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Machinify is a leading healthcare intelligence company with expertise across the payment continuum, delivering unmatched value, transparency, and efficiency to health plan clients across the country. Deployed by over 85 health plans, including many of the top 20, and representing more than 270 million lives, Machinify brings together a fully configurable and content-rich, AI-powered platform along with best-in-class expertise. We’re constantly reimagining what’s possible in our industry, creating disruptively simple, powerfully clear ways to maximize financial outcomes and drive down healthcare costs.Machinify is a leading healthcare intelligence company with expertise across the payment continuum, delivering unmatched value, transparency, and efficiency to health plan clients across the country. Deployed by over 85 health plans — including many of the top 20 and representing more than 270 million lives — Machinify brings together a fully configurable, content-rich, AI-powered platform along with best-in-class expertise. We're constantly reimagining what's possible in our industry, creating disruptively simple, powerfully clear ways to maximize financial outcomes and drive down healthcare costs. The Role We're building production-grade agentic systems that audit medical claims end-to-end — reading raw medical records, reasoning over coding and clinical guidelines, and producing defensible findings that hold up to clinical and regulatory review. Reaching human-expert accuracy on noisy, long-context documents is one of the hardest unsolved problems in applied AI, and the field is moving weekly. We're hiring an L4 AI Engineer who can step into an ambiguous problem, design an agent system from scratch, and ship it. You won't be plugging into someone else's architecture — you'll be deciding what the architecture should be. What You'll Do - Design agent systems from first principles. Decide the loop, the tools, the context strategy, the evaluation harness. Choose between single-agent and multi-agent topologies, between LLM reasoning and deterministic post-passes, between retrieval and direct context loading — and defend the choice with data. - Engineer the context. The hardest part of building a good agent is what goes into the prompt and what comes out. You'll obsess over context windows, tool surfaces, structured outputs, citation grounding, and the prompt itself. - Drive evaluation rigor. Build evals before you build the agent. Diagnose where it fails, fix the root cause, and prove the fix moved the metric. - Use AI tooling like a power user. A meaningful fraction of your day will be spent driving Claude Code, Codex, and similar tools to plan, scaffold, refactor, and debug your own work. We expect you to be faster with these tools than most engineers are without them. - Become a domain expert. Healthcare claims, coding guidelines, and the medical record itself are unavoidable parts of the job. Strong engineers who lean into the domain become outsized contributors here. What We're Looking For Required - 2–4 years of applied ML / AI engineering experience with a Bachelor's in CS, Math, Engineering or equivalent — or a Master's in a similar program with no prior industry experience required. Either way, at least one production-quality system (industry, research, or substantial open-source) you owned end-to-end. - Strong Python engineering. Clean abstractions, type discipline, async, tested code. - Deep, hands-on understanding of agent loops — how a model decides to call a tool, how a tool result re-enters context, how loops terminate, where they fail. - Hands-on experience with at least one major agent SDK — OpenAI Agents SDK, Anthropic SDK / claude-agent-sdk, LangGraph, or equivalent — and an opinion on the tradeoffs. - Working knowledge of how modern coding agents are built and how they engineer context — what goes in the system prompt, how files are read and edited, how long-running tasks are planned and tracked, where they break. - Fluency with Claude Code / Codex as a power user. You should be able to brainstorm, plan, and execute non-trivial engineering tasks with these tools — including reading their source when needed to understand or extend behavior. - Solid command of VS Code and git — branches, rebases, worktrees, conflict resolution, PR workflows. Not optional. - A bias toward measurement: you don't ship without an eval, and you don't believe a number you can't reproduce. Strongly preferred - Experience designing structured outputs (Pydantic / JSON Schema) and tool interfaces that LLMs reliably call correctly. - Familiarity with reasoning models (o-series, Claude extended thinking, Gemini thinking) and a sense of when they earn their cost. - Prior work on long-context, citation-grounded systems where the model must point to evidence, not just answer. - Healthcare, legal, finance, or any other domain where "mostly right" is unacceptable. Nice to have - Document understanding (OCR, layout-aware models, table extraction). - Vision-language models, multimodal retrieval. - Production experience with caching, observability, and cost control on LLM workloads. What We Offer  Work from anywhere in the US! Machinify is digital-first. Top Medical/Dental/Vision offerings FSA/HSA Tuition reimbursement Competitive salary, 401(k) with company match Unlimited PTO Additional health and wellness benefits and perks Flexible and trusting environment where you’ll feel empowered to do your best work  The salary for this position is based on an array of factors unique to each candidate: Such as years and depth of experience, set skills, certifications, etc. We are hiring for different levels and the base salary can range from $130k-$200k+ based on your assessed level. Compensation also includes meaningful equity, healthcare, unlimited PTO, and more.Equal Employment Opportunity at Machinify   We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status. We are proud to be an equal opportunity workplace. Machinify is an employment at will employer. We participate in E-Verify as required by applicable law. In accordance with applicable state laws, we do not inquire about salary history during the recruitment process. If you require a reasonable accommodation to complete any part of the application or recruitment process, please let our recruiters know. See our Candidate Privacy Notice at: https://www.machinify.com/candidate-privacy-notice/

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About Us: At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.Why Fireworks AI Fireworks AI is one of the fastest-growing companies in the AI infrastructure space. We built and operate the leading platform for both inference and training, the only place where teams can fine-tune frontier models and deploy them at production scale on a single platform. We are a Series C company valued at $4B, backed by Benchmark, Sequoia, Lightspeed, Index, and Evantic, and founded by veterans of Meta PyTorch and Google Vertex AI. In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice: Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog) Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog) The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) The Role: AI Field Engineers at Fireworks are the technical tip of the spear. You embed with our most ambitious customers and technology partners to turn complex AI problems into production systems, fast. The role sits at the intersection of engineering, product, and customer delivery. You are hands-on-keyboard building POCs, MVPs, and production integrations, while also holding your own in executive-level conversations about architecture, strategy, and business outcomes. You spend most of your time building. You ship code, run benchmarks, debug production issues, and architect deployments. But you also lead discovery conversations, align stakeholders, and translate customer pain points into product improvements that compress the feedback loop from field to roadmap. This is a role for engineers who are comfortable on-site with customers, building the relationships and trust that happen in person, not just over a call. The Segment As a Field Engineer in the AI Native segment you will work with the most innovative AI-native companies building at the frontier, where GenAI is the core product, not a feature, and where Fireworks is the platform they depend on to ship and scale it. These engagements move fast with fewer stakeholders, so you will spend more time in the code and iterate alongside their engineering teams, while still holding executive-level conversations on architecture and strategy. You will embed deeply with a small set of high-velocity accounts where the quality of your engineering is the relationship. What You'll Work On Technical Delivery and Deployment Build end-to-end POCs and MVPs alongside customer engineering teams, working inside their codebases, infrastructure, and constraints. For customers whose core product is built on GenAI, architect the inference foundations that capability depends on, and size deployments so they can scale in their market without infrastructure becoming the bottleneck. Run load tests and establish latency, throughput, and cost baselines against realistic customer traffic profiles, and tune deployments to hit those targets Deploy and validate new model families on inference frameworks (vLLM, SGLang), determining optimal shapes, quantization configs, and serving patterns across workloads. Model Strategy and Fine-Tuning Guide customers on model selection, fine-tuning strategy (SFT, DPO, RFT), and evaluation methodology. Build and run fine-tuning pipelines directly with customers, navigating trade-offs between model families, compute cost, and quality targets. Design and implement evaluation frameworks that measure production-quality metrics, not just benchmark scores. Customer Engagement and Stakeholder Management Many of our customers exist because of GenAI. Help them bake frontier model capabilities into their core offering and turn that into a durable competitive edge. Lead structured discovery conversations to unpack customer pain points, constraints, and success criteria before proposing solutions. Own the technical relationship from first engagement through production deployment. Embed with their engineering team as a peer, your credibility comes from what you build alongside them. Spend time on-site with customers. Build trust and momentum in person, embedding with their teams where the work happens. Product Feedback and Platform Improvement Identify recurring customer pain points and translate them into concrete product proposals, working directly with engineering and product to ship fixes and features. Codify repeatable deployment patterns and contribute them back to internal tooling, documentation, and the platform itself. Feed customer signals (deployment patterns, failure modes, feature gaps) back into the product roadmap with specificity and urgency. What We're Looking For: Minimum Qualifications 5+ years in a hands-on, customer-facing technical role: Forward Deployed Engineer, Applied AI Engineer, Solutions Architect, ML Engineer with field exposure, or technical founder. Demonstrated ability to build production software with customers, not just advise on it. You have shipped code running in someone else's production environment. Strong Python skills. Comfortable reading, writing, and debugging production code. Familiarity with Kubernetes and infrastructure engineering. Working knowledge of the LLM stack: inference trade-offs, model serving, fine-tuning workflows (SFT at minimum; DPO/RFT a strong plus). Experience with cloud infrastructure (AWS, Azure, GCP) and deploying models on GPU infrastructure. Exceptional communication: able to run a sharp discovery call, present to a VP, and debug a latency issue with an ML engineer in the same afternoon. Experience building or integrating agentic systems, tool-use chains, or AI-native developer toolchains. Preferred Qualifications 10+ years in technical field or engineering roles. Experience with inference serving frameworks (vLLM, SGLang, TensorRT-LLM) and tuning deployments for real workloads. Prior experience at a company with a forward-deployed or embedded engineering model (Palantir, Scale AI, Anthropic, OpenAI, BCG X, McKinsey Quantum Black, AI Native startups with FDE motions). Prior experience as a technical founder or early engineer at an AI-native company is a strong signal. Track record taking GenAI POCs from prototype to production-scale deployments. Experience with hyperscaler AI platforms (Azure AI Foundry, AWS Bedrock/SageMaker, GCP Vertex). Total compensation for this role also includes meaningful equity in a fast-growing startup, along with a competitive salary and comprehensive benefits package. Base salary is determined by a range of factors including individual qualifications, experience, skills, interview performance, market data, and work location. The listed salary range is intended as a guideline and may be adjusted.On Target Earnings (Plus Equity)$200,000—$260,000 USDWhy Fireworks AI? Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving. Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally. Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results. Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation. Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.

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About the TeamTraining Runtime builds the distributed systems that power OpenAI's largest model training runs - most recently GPT-5.5! The Data Movement area owns the infrastructure that keeps training jobs supplied with the right data at the right time, and keeps model state moving safely and efficiently across large clusters.Our work spans machine learning systems, distributed storage, high-throughput data loading, reliability engineering, and developer experience. Success means researchers can move quickly while training runs remain fast, reproducible, debuggable, and resilient at scale.About the RoleWe are looking for a deeply hands-on Technical Lead Manager to own datasets throughout our training infrastructure. This person will set the direction for how training jobs read data: the APIs, storage contracts, versioning model, benchmarks, debugging tools, and reliability guarantees that make data access consistent across current and future training frameworks.You will begin as the primary technical owner for dataset reads, working directly in the code while aligning researchers, training framework owners, storage teams, and infrastructure partners around a durable platform. The problem is deceptively hard at frontier scale: make enormous, heterogeneous datasets easy to consume, fast to restart, correct across distributed workers, observable when something goes wrong, and flexible enough to support pretraining, reinforcement learning, and multimodal training.In this role, you willDesign and build a unified dataset read platform for multiple current and future training frameworks.Define dataset APIs, storage-format expectations, registration/versioning, and migration paths that make data access reproducible and maintainable.Build reliability into the read path, including stateful iteration, caching, fast restart, recovery, and clear operational contracts.Build terminal and web-based visualizers that let teams inspect text, multimodal, and reinforcement learning data late in the pipeline, where bugs are most visible.Write and review production code in core data loading, service, caching, and reliability paths.Partner with teams working on training frameworks, reinforcement learning, multimodal models, storage, runtime, and cluster infrastructure.Over TimeThe long-term goal is a team that owns fast, correct, scalable, and reliable in-cluster data movement for training: data that comes in, data that goes out, and data that moves around inside the cluster. After ramping on datasets, this role will expand to TLM ownership for broader data movement systems, including checkpoint loads/saves and snapshot transfers, while partnering closely with existing technical leads and adjacent infrastructure teams.You might thrive in this role if you:Have built or owned dataset, data loading, storage, or distributed training infrastructure at large scale (e.g. torch.utils.data)Care equally about API design, debugging ergonomics, performance, and bit-level correctness.Understand the failure modes of large distributed training jobs and know how data systems can create or prevent them.Have experience with stateful iterators, checkpoint/restart semantics, caching, remote services, or high-throughput storage reads.Are comfortable working across Python and lower-level systems code; Rust or C++ experience is useful but not required.Have worked with multimodal, video, reinforcement learning, or pretraining data pipelines where small data bugs are expensive and hard to diagnose.Can lead through code and technical judgment before a team exists, and can later manage engineers without losing the hands-on edge.Obsess over developer experience by eliminating friction, such as manual preprocessing scripts and niche cluster-specific bugs, ensuring a reliable and efficient experience for researchers.About OpenAIOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.OpenAI Global Applicant Privacy PolicyAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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About the TeamThe ChatGPT organization at OpenAI supports our mission by bringing advanced AI capabilities to hundreds of millions of users worldwide. The Image Generation team is responsible for one of the fastest-growing experiences in ChatGPT, enabling users to create, edit, and transform images through natural language. Recent advances in our multimodal image models have dramatically improved image quality, instruction following, editing precision, consistency, and text rendering, unlocking entirely new creative and professional workflows.We work at the intersection of research, infrastructure, and product to build the systems that power image generation at global scale. Our team partners closely with researchers, product engineers, designers, and platform teams to bring state-of-the-art image capabilities to millions of users while continuously pushing the boundaries of what AI-powered creation can do.About the RoleWe are looking for an experienced Backend Engineer to join the Image Generation team and help build the systems that power image creation and editing across ChatGPT.You'll work on the core backend infrastructure that enables users to generate, edit, and iterate on visual content using cutting-edge multimodal AI models. This includes building highly scalable services, orchestration systems, APIs, storage platforms, and distributed infrastructure that support billions of image generations and editing workflows. You'll partner closely with product, research, and mobile teams to transform breakthrough AI capabilities into reliable, performant experiences used by millions around the world.In this role, you will:Design, build, and operate backend systems that power image generation and image editing experiences in ChatGPT.Develop scalable APIs, services, and infrastructure that support multimodal AI workflows.Optimize reliability, latency, throughput, and cost across large-scale distributed systems.Partner with researchers to productionize new image generation capabilities and bring them to users quickly and safely.Collaborate closely with Android, iOS, web, and full-stack engineers to build seamless end-to-end product experiences.Drive technical architecture decisions across storage, serving, orchestration, and platform systems.Use data and experimentation to identify opportunities for improving user experience, performance, and system efficiency.Help shape engineering culture through technical leadership, mentorship, and operational excellence.You might thrive in this role if you:Have experience building and operating large-scale backend or distributed systems.Have strong proficiency in modern backend technologies and cloud-native architectures.Enjoy working across the stack and partnering closely with product and research teams.Have experience designing APIs, service-oriented architectures, and highly reliable production systems.Are highly analytical and enjoy using data to inform technical and product decisions.Have a strong sense of ownership and are comfortable navigating ambiguity in fast-moving environments.Are excited by multimodal AI and the opportunity to help define the infrastructure powering the future of visual creation.Have a deep curiosity about how cutting-edge AI research can be translated into products that reach millions of users.About OpenAIOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.OpenAI Global Applicant Privacy PolicyAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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About the TeamThe ChatGPT organization at OpenAI supports our mission by bringing advanced AI capabilities to hundreds of millions of users worldwide. The Image Generation team is responsible for one of the fastest-growing experiences in ChatGPT, enabling users to create, edit, and transform images through natural language.Recent breakthroughs in multimodal AI have dramatically improved image quality, instruction following, editing precision, consistency, and text rendering. We're building the systems and experiences that turn these research advances into products used daily by creators, professionals, businesses, and consumers around the world.Our team sits at the intersection of research, product, design, and infrastructure. We work closely with model researchers, mobile engineers, frontend engineers, and platform teams to build intuitive experiences and scalable systems that power image generation at global scale. Whether users are creating marketing assets, visualizing ideas, editing photos, designing products, or simply exploring their creativity, our goal is to make visual creation feel as natural as having a conversation.About the RoleWe are looking for an experienced Full Stack Engineer to join the Image Generation team and help shape the future of AI-powered visual creation.In this role, you'll own features end-to-end across both frontend and backend systems, building the experiences that enable users to generate, edit, organize, and interact with images inside ChatGPT. You'll work across the entire stack—from highly interactive user interfaces and real-time workflows to backend services, APIs, orchestration systems, and data infrastructure.This role is ideal for engineers who enjoy moving fluidly between product development and systems engineering, collaborating closely with design, product, and research teams to rapidly bring new AI capabilities to users. You'll help define entirely new interaction paradigms as multimodal AI continues to evolve.In this role, you will:Design, build, and launch end-to-end product experiences for image generation and image editing within ChatGPT.Develop highly interactive frontend experiences that make sophisticated AI capabilities feel intuitive, fast, and delightful.Build scalable backend services, APIs, and workflows that power image creation, editing, storage, sharing, and retrieval.Partner closely with researchers to rapidly prototype and productionize new multimodal capabilities.Collaborate with Product, Design, Data Science, and Engineering teams to identify high-impact opportunities and execute against them.Own projects from concept through launch, including technical design, implementation, experimentation, measurement, and iteration.Optimize performance across the stack, from frontend responsiveness and rendering to backend latency, reliability, and scalability.Design systems that can support millions of users generating and interacting with visual content simultaneously.Leverage experimentation and user insights to improve engagement, usability, quality, and product outcomes.Contribute to engineering best practices around architecture, testing, observability, developer productivity, and operational excellence.Help define the future roadmap for AI-powered creative tools and visual experiences.You might thrive in this role if you:Have experience building and shipping production-grade applications across both frontend and backend systems.Are comfortable working with modern web technologies such as React, TypeScript, and contemporary frontend frameworks.Have experience building scalable backend services, APIs, and distributed systems.Enjoy owning products end-to-end and can seamlessly move between user experience challenges and infrastructure decisions.Have strong product instincts and enjoy thinking deeply about how users interact with technology.Are highly analytical and comfortable using experimentation, metrics, and user feedback to drive decision-making.Thrive in fast-moving environments where priorities evolve quickly and new opportunities emerge constantly.Enjoy collaborating with cross-functional partners including researchers, designers, product managers, and data scientists.Are excited by multimodal AI and motivated by the opportunity to define entirely new ways for people to create and communicate visually.Have experience with media platforms, creative tools, image processing, content creation products, or AI-powered applications (a plus).Why this role is uniqueImage Generation sits at the center of some of the most exciting advances happening in AI today. As a Full Stack Engineer on the team, you'll have the opportunity to work across the entire product surface, influence both user experience and technical architecture, and help bring cutting-edge multimodal research to hundreds of millions of users. The problems are highly visible, technically challenging, and deeply impactful—spanning product innovation, distributed systems, AI integration, and large-scale user experiences.About OpenAIOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.OpenAI Global Applicant Privacy PolicyAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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Our MissionReflection’s mission is to build open superintelligence and make it accessible to all.We’re developing open weight models for individuals, agents, enterprises, and even nation states. Our team of AI researchers and company builders come from DeepMind, OpenAI, Google Brain, Meta, Character.AI, Anthropic and beyond.Role OverviewWe’re looking for a core member of Reflection’s Applied AI team to drive our Forward Deployed Engineering efforts with enterprise customers. This team works hands-on to translate advanced AI research into high-impact, real-world applications. As a Forward Deployed Engineer, you will own the technical strategy and delivery of agentic systems from initial customer discovery through production launch.What You'll DoPartner with Deployment Strategists and Sales to understand enterprise customer needs, architect solutions, and develop transformative agentic applications.Build agentic systems using state-of-the-art models, orchestrating LLM workflows, integrating with enterprise infrastructure, and deploying reliable production systems.Collaborate with research teams to adapt and fine-tune models for customer-specific needs.Support end-to-end deployments across hybrid environments (public cloud, VPC, and on-premises), helping ensure scalability, performance, and reliability in production.Contribute to evolving playbooks, processes, and best practices as part of a growing Forward Deployed Engineering organization.What We're Looking ForStrong software engineering background with experience shipping production-grade systems (Python, Typescript)Proven track record of deploying enterprise software in cloud or hybrid environments using modern DevOps practices (Docker, Kubernetes, and CI/CD).Deep understanding of machine learning concepts and hands-on experience with modern AI stacks, including vector databases, RAG pipelines, agent orchestration, evaluations, and fine-tuning.3+ years of software engineering experience delivering AI-driven enterprise solutions (e.g., Forward Deployed Engineer, Software Engineer, or Applied AI Engineer).Demonstrated ability and interest to work in customer-facing environments, understanding user needs, architecting solutions for real business problems, and delivering tangible outcomes.Self-starter with high agency and ownership, excelling in fast-paced startup environments where playbooks are still being written.What We Offer:We believe that to build superintelligence that is truly open, you need to start at the foundation. Joining Reflection means building from the ground up as part of a small talent-dense team. You will help define our future as a company, and help define the frontier of open foundational models.We want you to do the most impactful work of your career with the confidence that you and the people you care about most are supported.Top-tier compensation: Salary and equity structured to recognize and retain the best talent globally.Health & wellness: Comprehensive medical, dental, vision, life, and disability insurance.Life & family: Fully paid parental leave for all new parents, including adoptive and surrogate journeys. Financial support for family planning.Benefits & balance: paid time off when you need it, relocation support, and more perks that optimize your time. Opportunities to connect with teammates: lunch and dinner are provided daily. We have regular off-sites and team celebrations.

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Our MissionReflection’s mission is to build open superintelligence and make it accessible to all.We’re developing open weight models for individuals, agents, enterprises, and even nation states. Our team of AI researchers and company builders come from DeepMind, OpenAI, Google Brain, Meta, Character.AI, Anthropic and beyond.Role OverviewWe’re seeking an exceptional technical lead to build and scale Reflection’s Forward Deployed Engineering function within the AI Solutions team. This team plays a critical role in bridging our cutting-edge AI research with real-world enterprise deployments. As a Forward Deployed Engineer Lead, you will own the end-to-end technical strategy, execution, and delivery of complex agentic applications, from early pre-sales discovery through production deployment.What You'll DoPartner with Deployment Strategists and Sales to understand enterprise customer needs, architect solutions, and develop transformative agentic applications.Architect and build complex agentic systems using state-of-the-art models, orchestrating sophisticated LLM workflows and integrating deeply with enterprise infrastructure.Collaborate with research teams to adapt and fine-tune models for customer-specific needs, contributing to our internal codebase for inference, fine-tuning, and evaluation.Own end-to-end deployments across hybrid environments (public cloud, VPC, and on-premises), ensuring production-grade scalability, performance, and reliability.Shape and scale the Forward Deployed Engineering organization by defining playbooks, best practices, technical standards, and mentorship to support team growth.What We're Looking ForStrong software engineering background with experience shipping production-grade systems (Python, Typescript)Proven track record of deploying enterprise software in cloud or hybrid environments using modern DevOps practices (Docker, Kubernetes, and CI/CD).Deep understanding of machine learning concepts and hands-on experience with modern AI stacks, including vector databases, RAG pipelines, agent orchestration, evaluations, and fine-tuning.6+ years of software engineering experience, including 2+ years in a technical leadership capacity delivering AI-driven enterprise solutions (e.g., Lead Forward Deployed Engineer, Tech Lead, or Engineering Manager).Demonstrated ability and interest to work in customer-facing environments, understanding user needs, architecting solutions for real business problems, and delivering tangible outcomes.Self-starter with high agency and ownership, excelling in fast-paced startup environments where playbooks are still being written.What We Offer:We believe that to build superintelligence that is truly open, you need to start at the foundation. Joining Reflection means building from the ground up as part of a small talent-dense team. You will help define our future as a company, and help define the frontier of open foundational models.We want you to do the most impactful work of your career with the confidence that you and the people you care about most are supported.Top-tier compensation: Salary and equity structured to recognize and retain the best talent globally.Health & wellness: Comprehensive medical, dental, vision, life, and disability insurance.Life & family: Fully paid parental leave for all new parents, including adoptive and surrogate journeys. Financial support for family planning.Benefits & balance: paid time off when you need it, relocation support, and more perks that optimize your time. Opportunities to connect with teammates: lunch and dinner are provided daily. We have regular off-sites and team celebrations.

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Crusoe is on a mission to accelerate the abundance of energy and intelligence. As the only vertically integrated AI infrastructure company built from the ground up, we own and operate each layer of the stack — from electrons to tokens — to power the world's most ambitious AI workloads. When you join Crusoe, you join a team that is building the future, faster.We're in the midst of the greatest industrial revolution of our time. The demand for AI compute is boundless, and power is a bottleneck. We're solving that — with an energy-first approach that makes AI infrastructure better for the world and faster for the people innovating with AI.We're looking for problem-solving, opportunity-finding teammates with a sense of urgency, who believe in the scale of our ambition and thrive on a path not fully paved — people who want to grow their careers alongside a team of experts across energy, manufacturing, data center construction, and cloud services.If you want to do the most meaningful work of your career, help our customers and partners advance their AI strategies, and be part of a high-performing team that believes in each other, come build with us at Crusoe.About the Role:Join Crusoe as a Senior Engineering Manager and lead a talented team focused on revolutionizing our cloud infrastructure. In this pivotal role, you'll lead the Command Center Insights & Actions team — building the systems that translate raw infrastructure telemetry into human-readable diagnostics and automated remediation workflows. You'll own a technical roadmap spanning alerting engines, heuristic development, node health systems, and state machines that trigger proactive maintenance without impacting customer workloads, while exploring the integration of Large Language Models (LLMs) to build cutting-edge AI solutions within our Command Center product. This is a full-time opportunity for a passionate leader who thrives on building high-performing teams, fostering innovation, and delivering impactful, data-driven solutions in a dynamic environment.What You'll Be Working On:Drive the Insights & Actions Roadmap: Own and execute across alerting infrastructure, control plane APIs, automated action systems, and telemetry-derived insights such as straggler node detection and GPU profiling.Influence Strategic Roadmaps: Contribute significantly to the team's roadmap, impacting long-term team goals and operational performance metrics.Refine Early Product Requirements: Collaborate with product and engineering leadership to bring clarity to ambiguous problems early in the scoping process.Collaborate Cross-Functionally: Partner with product, design, and engineering teams inside and outside the organization to align on goals and deliver integrated solutions.Manage Complex Projects: Lead critical initiatives involving multiple engineers, including those outside your direct report structure, ensuring customer outcomes are auditable and decisions are data-driven.Drive Technical Excellence: Champion process improvements, operational excellence, and best practices across the team.Cultivate Team Growth: Coach and mentor engineers from new grad to Staff level, setting clear performance expectations and defining career paths to build a high-performing, sustainable team.What You'll Bring to the Team:Technical Expertise in Observability & Intelligence Systems: Hands-on background in ML, heuristics, or rule-based systems — with the ability to engage deeply on problems like anomaly detection, threshold design, and automated remediation logic.Proven Leadership: Demonstrated track record of people management, leading with empathy, and maintaining a sustainable workload for your teams.Technical Acumen: Ability to lead effectively in spaces where problems, opportunities, and strategies are not yet fully defined — driving clarity, direction, and execution.Cross-Functional Collaboration: Excellent technical communication skills, both verbal and written, to work effectively across diverse roles and functions.Project Ownership: Proven experience owning and delivering complex projects end-to-end, with measurable quality and data-driven decision-making.Global Scale Experience: Background building and operating global services at scale.Organizational Prowess: Highly organized and capable of managing multiple complex initiatives and team priorities in parallel.Bonus PointsBackground in data platforms and data scienceBackground in observability platforms or productsFamiliarity with GPU profiling tools (Nsight, NCCL Inspector) or infrastructure diagnostics at the hardware layerHighly motivated and proactive in identifying process improvements and boosting team efficiencyPassion for coaching and mentoring engineers into high-performing individualsEnthusiasm for building team culture with a high quality of life for engineersA true "people-person" who thrives in collaborative environments and is energized by teamworkBenefits:Competitive compensation and equity packagesRestricted Stock UnitsPaid time off, paid holidays & leave of absence programsComprehensive health, dental & vision insuranceEmployer contributions to HSA accountPaid parental leavePaid life insurance, short-term and long-term disabilityProfessional development & tuition reimbursementMental health & wellness supportCommuter benefits (parking & transit)Cell phone stipend401(k) Retirement plan with company match up to 4% of salaryVolunteer time offGlobal travel insurance & emergency assistanceDaily meals allowanceAdditional perks & programs specific to locationCompensation RangeCompensation will be paid in the range of up to $245,000 -$295,000 + Bonus. Restricted Stock Units are included in all offers. Compensation to be determined by the applicant's knowledge, education, and abilities, as well as internal equity and alignment with market data.Crusoe is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, disability, genetic information, pregnancy, citizenship, marital status, sex/gender, sexual preference/ orientation, gender identity, age, veteran status, national origin, or any other status protected by law or regulation.

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About ElevenLabsElevenLabs is an AI research and product company transforming how we interact with technology.We launched in January 2023 with the first human-like AI voice model. Today, we serve millions of users and thousands of businesses - from fast-growing startups to large enterprises like Deutsche Telekom and Meta. Our investors are some of the world's most prominent, including Andreessen Horowitz, ICONIQ Growth and Sequoia. We've raised $781M in funding and our last valuation was $11B - multiples of 11, always. We have expanded from voice into three main platforms:ElevenAgents enables businesses to deliver seamless and intelligent customer experiences, with the integrations, testing, monitoring, and reliability necessary to deploy voice and chat agents at scale.ElevenCreative empowers creators and marketers to generate and edit speech, music, image, and video across 70+ languages.ElevenAPI gives developers access to our leading AI audio foundational models.Everything we do is the result of the creativity and commitment of our team - builders doing the best work of their lives. We are researchers, engineers, and operators. IOI medalists and ex-founders. If you want to work hard and create lasting positive impact, we want to hear from you.How we workHigh-velocity: Rapid experimentation, lean autonomous teams, and minimal bureaucracy.Impact not job titles: We don’t have job titles. Instead, it’s about the impact you have. No task is above or beneath you.AI first: We use AI to move faster with higher-quality results. We do this across the whole company—from engineering to growth to operations.Excellence everywhere: Everything we do should match the quality of our AI models.Global team: We prioritize your talent, not your location.What we offerInnovative culture: You’ll be part of a generational opportunity to define the trajectory of AI, surrounded by a team pushing the boundaries of what’s possible.Growth paths: Joining ElevenLabs means joining a dynamic team with countless opportunities to drive impact - beyond your immediate role and responsibilities.Learning & development: ElevenLabs proactively supports professional development through an annual discretionary stipend.Social travel: We also provide an annual discretionary stipend to meet up with colleagues each year, however you choose.Annual company offsite: Each year, we bring the entire team together in a new location - past offsites have included Croatia and Italy.Co-working: If you’re not located near one of our main hubs, we offer a monthly co-working stipend.About the roleAs a Forward Deployed Engineer Strategist, you'll work as part of a driven and creative team of Engineers, Product Designers, and other Strategists to deploy our voice AI technology against the most challenging problems our customers face. Your mission is to synthesize disconnected streams of thought into a cohesive understanding of what the most important problem is, what the data means, what the product needs, what users are motivated by, and where the impact could be.No two days are the same, but as a FDE Strategist you can expect to:Meet with strategic customers to understand their critical audio and voice AI needs and locate their biggest pain points.Identify relevant use cases through deep engagement with customer problems and workflows, and work with Engineers to implement our voice and audio AI technology into innovative solutions.Design and architect bespoke integrations for customers, ensuring our technology fits seamlessly into their products and operations.Guide customers on best practices for implementing our voice and audio AI models to maximize their effectiveness.Present the results of our work and proposals for future work to audiences ranging from technical teams to C-suite executives.Collaborate with our Research and Product teams to incorporate field insights into ElevenLabs' software products and AI models.Build and deliver compelling demos of our voice and audio AI technology to new and existing customers.Scope out potential applications in new industries and expand our AI solutions across different sectors globally.Take full ownership of end-to-end execution of major projects for our most strategic partners, working hands-on to deliver high-impact solutions.Collaborate daily with our customers' engineering and executive teams to ensure optimal implementation of ElevenLabs' technologies.RequirementsExperience working with customers in a technical capacity. It's ok if you only worked with customers in student clubs or side projects, as long as you are interested in working closely with them.Basic proficiency in Python and understanding of API integration to implement scripts and help with prototyping/demo building.Excellent communication and problem-solving skills, especially in terms of ability to summarize complex technical concepts and using logic in pursuing optimal solutions.A proven track record of taking ownership of complex projects and delivering results.Adaptability to work across different customer environments and technical use cases.Technical aptitude to quickly understand our voice and audio AI models and their applications.LocationThe candidate should preferably be based in the Netherlands, and be able to come in-office multiple days a week.

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Founded in 2015, Shield AI is a venture-backed deep-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include the V-BAT and X-BAT aircraft, Hivemind Enterprise, and the Hivemind Vision product lines. With offices and facilities across the U.S., Europe, the Middle East, and the Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube.  The Autonomous Pilot Integration team builds autonomy solutions for a wide range of CONOPs and mission sets. We combine capabilities from the Autonomy Capabilities team (motion planning, tactics), the Perception team (e.g., track fusion), and the HivemindSDK to develop the autonomy software that runs on an unmanned platform — air, maritime, space, or effects/expendables, depending on the program — then integrate, validate, and field it on the real hardware. In this role, you'll write new autonomy code — such as mission behaviors, platform-specific control, multi-agent coordination, contingencies, and executive autonomy — and own it end-to-end from software-in-the-loop, to hardware-in-the-loop, to vehicle-in-the-loop, to live test exercise. You'll partner closely with the Autonomy Capabilities and Perception teams, feature crews, and external platform integrators (vehicle/autopilot control vendors, C2 providers). It's a hands-on role for engineers who like seeing their code operate in the real world — whether that's flying, sailing, orbiting, or downrange — and want to be there when it does.  At this level, you'll also serve as a technical leader within the team — leading a small feature crew or sub-program through design, integration, and delivery, mentoring mid-level engineers, and representing the team directly to capability teams and external partners.  Shield AI is committed to developing cutting-edge autonomy for unmanned platforms across every operating domain — air, maritime, space, and effects/expendables — in service of the U.S. Department of Defense and our international defense customers. Our Autonomous Pilot Integration engineers bridge the gap between R&D and deployment, ensuring autonomous systems function reliably and effectively wherever and whenever they're needed most.  What You'll Do: Develop & Field Autonomy — Develop & integrate autonomy software solutions onto unmanned platforms (air, maritime, space, or effects/expendables), including payload computer bring-up, container-based deployment (e.g., k3s/k3d), and configuration across onboard compute, sensors, and command-and-control interfaces — and lead a small team through the design, development, and delivery of a major capability or sub-program.  Technical Leadership — Lead a small feature crew or sub-program; set technical direction, break down work, unblock the team, and report progress to leadership and stakeholders.  Collaboration Across Teams — Act as a primary technical interface with the Autonomy Capabilities team (motion planning, tactics), the Perception team, feature crews, and external partners (platform integrators, vehicle/autopilot control vendors, C2 providers); author and negotiate ICDs and interface contracts rather than just consume them  Mentorship & Growth — Mentor mid-level engineers on the team; partner with managers on onboarding, leveling, and growth planning. Formally onboard senior new hires.  Design & Documentation — Drive design reviews, ICDs, and post-mortems for your area; push the team toward higher rigor and close process gaps that span teams.  Pre-deployment Preparation — Own the build, configuration, and validation process for mission-ready systems; coordinate hardware/software compatibility, mission readiness, and release cadence with capability and feature teams.  On-site Test & Mission Support — Travel to test sites and support live mission operations (flight tests, range exercises, on-water trials, integration events), including safety checks, system bring-up, and troubleshooting under time-critical constraints.  Hardware/Software Debugging — Diagnose and resolve integration issues across complex autonomy stacks, payload computers, and embedded systems in lab and field environments — including memory, CPU, and timing profiling under operationally-representative loads.  Mission Data & Debrief Support — Capture mission and test data, reproduce issues in simulation, and partner with autonomy capability owners to drive fixes back into the next build.  Continuous Improvement — Build tools and processes to improve integration timelines, test/mission reliability, and team efficiency across deployment cycles.  C2 Interoperability & Standards — Own the interface contracts with C2 providers and drive standards compliance for your area, including implementation and validation against command-and-control standards (e.g., A-GRA, UCI, OMS).  Hiring — Interview candidates, help define the skills bar for open roles in your area, and onboard new engineers into your sub-program.  Travel Requirement – Members of this team typically travel around 10-20% of the year (to different office locations, customer sites, and integration/test events).  Required Qualifications: BS/MS in Computer Science, Electrical Engineering, Mechanical Engineering, Aerospace Engineering, and/or similar degree, or equivalent practical experience  Typically requires a minimum of 7 years of related experience with a Bachelor’s degree; or 5 years and a Master’s degree; or 4 years with a PhD; or equivalent work experience.  Proficiency in C++, with experience developing or integrating real-time or latency-sensitive systems.  Proficiency in Linux-based development and experience working with embedded systems, shell scripting, and system diagnostics.  Familiarity with middleware, pub-sub, or IPC frameworks used in autonomy or robotics systems (e.g., DDS, message buses).  Hands-on experience supporting demos, exercises, or field/mission tests for unmanned or autonomous systems.  Experience with autonomy simulation environments for testing and validation.  Demonstrated experience leading a small technical team or owning a major capability from design through field delivery.  Track record of mentoring engineers and growing technical talent.  Experience authoring or negotiating interface contracts / ICDs with internal or external stakeholders.  Strong problem-solving skills, with the ability to troubleshoot and optimize system performance across the full stack.  Excellent communication and teamwork skills, with the ability to work effectively in a collaborative, multidisciplinary environment.  Ability to obtain a SECRET clearance.  Preferred Qualifications: Direct experience supporting unmanned systems (air, maritime, space, ground, or effects/expendables) or similar field test campaigns.  Proficiency in Python for scripting, automation, and analysis.  Experience leading a feature crew, sub-program, or small team in an unmanned systems context.  Experience owning customer- or partner-facing technical relationships (e.g., autopilot vendors, C2 providers, government program offices).  Track record of cross-team improvements (process, rigor, documentation, or developer experience).  Familiarity with autonomy stacks, motion planning, or vehicle-control integration.  Competence in vehicle electronics bring-up (avionics, spacecraft buses, or vessel control), payload computer integration, or hardware-in-the-loop debugging.  Experience with container orchestration (e.g., k3s, k3d, Docker) on embedded or payload compute.  Familiarity with platform control / autopilot stacks (e.g., PX4, ArduPilot, spacecraft flight software, vessel autopilots).  Proficiency in developing automation tools for system testing, logging, and data parsing.  Build-system experience (e.g., Conan, CMake) and CI/CD pipeline familiarity.  Comfortable interfacing with DoD stakeholders during field events or technical reviews.  Experience with C2 standards such as A-GRA, UCI, or OMS.  Familiarity with government-furnished simulation environments (e.g., AFSIM, NGTS) is a plus.  187,531 - 281,297 a year #LI-ED1 #LD Full-time regular employee offer package: Pay within range listed + Bonus + Benefits + Equity Temporary employee offer package: Pay within range listed above + temporary benefits package (applicable after 60 days of employment) Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information. ### Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know. 

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Founded in 2015, Shield AI is a venture-backed deep-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include the V-BAT and X-BAT aircraft, Hivemind Enterprise, and the Hivemind Vision product lines. With offices and facilities across the U.S., Europe, the Middle East, and the Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube.  The Autonomous Pilot Integration team builds autonomy solutions for a wide range of CONOPs and mission sets. We combine capabilities from the Autonomy Capabilities team (motion planning, tactics), the Perception team (e.g., track fusion), and the HivemindSDK to develop the autonomy software that runs on an unmanned platform — air, maritime, space, or effects/expendables, depending on the program — then integrate, validate, and field it on the real hardware. In this role, you'll write new autonomy code — such as mission behaviors, platform-specific control, multi-agent coordination, contingencies, and executive autonomy — and own it end-to-end from software-in-the-loop, to hardware-in-the-loop, to vehicle-in-the-loop, to live test exercise. You'll partner closely with the Autonomy Capabilities and Perception teams, feature crews, and external platform integrators (vehicle/autopilot control vendors, C2 providers). It's a hands-on role for engineers who like seeing their code operate in the real world — whether that's flying, sailing, orbiting, or downrange — and want to be there when it does.  Shield AI is committed to developing cutting-edge autonomy for unmanned platforms across every operating domain — air, maritime, space, and effects/expendables — in service of the U.S. Department of Defense and our international defense customers. Our Autonomous Pilot Integration engineers bridge the gap between R&D and deployment, ensuring autonomous systems function reliably and effectively wherever and whenever they're needed most.  What You'll Do: Develop & Field Autonomy — Develop & integrate autonomy software solutions onto unmanned platforms (air, maritime, space, or effects/expendables), including payload computer bring-up, container-based deployment (e.g., k3s/k3d), and configuration across onboard compute, sensors, and command-and-control interfaces.  Collaboration Across Teams — Work closely with the Autonomy Capabilities team (motion planning, tactics), the Perception team, feature crews, and external partners (platform integrators, vehicle/autopilot control vendors, C2 providers) to deliver and validate mission-critical functionality on time.  Pre-deployment Preparation — Own the build, configuration, and validation process for mission-ready systems; coordinate hardware/software compatibility, mission readiness, and release cadence with capability and feature teams.  On-site Test & Mission Support — Travel to test sites and support live mission operations (flight tests, range exercises, on-water trials, integration events), including safety checks, system bring-up, and troubleshooting under time-critical constraints.  Hardware/Software Debugging — Diagnose and resolve integration issues across complex autonomy stacks, payload computers, and embedded systems in lab and field environments — including memory, CPU, and timing profiling under operationally-representative loads.  Mission Data & Debrief Support — Capture mission and test data, reproduce issues in simulation, and partner with autonomy capability owners to drive fixes back into the next build.  Continuous Improvement — Build tools and processes to improve integration timelines, test/mission reliability, and team efficiency across deployment cycles.  C2 Interoperability & Standards — Implement and validate compliance with command-and-control standards (e.g., A-GRA, UCI, OMS) and coordinate with C2 providers on interface contracts and integration milestones.  Travel Requirement – Members of this team typically travel around 10-20% of the year (to different office locations, customer sites, and integration/test events).  Required Qualifications: BS/MS in Computer Science, Electrical Engineering, Mechanical Engineering, Aerospace Engineering, and/or similar degree, or equivalent practical experience  Typically requires a minimum of 5 years of related experience with a Bachelor’s degree; or 4 years and a Master’s degree; or 2 years with a PhD; or equivalent work experience.  Proficiency in C++, with experience developing or integrating real-time or latency-sensitive systems.  Proficiency in Linux-based development and experience working with embedded systems, shell scripting, and system diagnostics.  Familiarity with middleware, pub-sub, or IPC frameworks used in autonomy or robotics systems (e.g., DDS, ActiveMQ).  Hands-on experience supporting demos, exercises, or field/mission tests for unmanned or autonomous systems.  Experience with autonomy simulation environments for testing and validation.  Strong problem-solving skills, with the ability to troubleshoot and optimize system performance across the full stack.  Excellent communication and teamwork skills, with the ability to work effectively in a collaborative, multidisciplinary environment.  Ability to obtain a SECRET clearance.  Preferred Qualifications: Direct experience supporting uncrewed systems (air, maritime, space, ground, or effects/expendables) or similar field test campaigns.  Proficiency in Python for scripting, automation, and analysis.  Familiarity with autonomy stacks, motion planning, or vehicle-control integration.  Competence in vehicle electronics bring-up (avionics, spacecraft buses, or vessel control), payload computer integration, or hardware-in-the-loop debugging.  Experience with container orchestration (e.g., k3s, k3d, Docker) on embedded or payload compute.  Familiarity with platform control / autopilot stacks (e.g., PX4, ArduPilot, spacecraft flight software, vessel autopilots).  Proficiency in developing automation tools for system testing, logging, and data parsing.  Build-system experience (e.g., Conan, CMake) and CI/CD pipeline familiarity.  Comfortable interfacing with DoD stakeholders during field events or technical reviews.  Experience with C2 standards such as A-GRA, UCI, or OMS.  Familiarity with government-furnished simulation environments (e.g., AFSIM, NGTS) is a plus.  160,000 - 240,000 a year #LI-ED1 #LC Full-time regular employee offer package: Pay within range listed + Bonus + Benefits + Equity Temporary employee offer package: Pay within range listed above + temporary benefits package (applicable after 60 days of employment) Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information. ### Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know. 

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About HandshakeHandshake was founded on a simple belief that everyone deserves a path to a great career, regardless of where they went to school or who they know. Today, we power 25 million job seekers, 1 million+ employers, and 1,600 educational institutions.In 2025, we started Handshake AI and built the fastest-growing AI data business in history. We work directly with frontier AI lab researchers to create evaluations, publish benchmarks, and push the boundary of data. We’ve grown from $0 to ~$1B run rate and pay ~$60M to over 30K individuals every month. Why join Handshake now:Shape how every career evolves in the AI economy, at global scale, with impact your friends, family and peers can see and feelPartner hand-in-hand with world-class AI labs, Fortune 500 partners and the world’s top educational institutionsWork together with engineers, scientists, operators, and more from Palantir, Meta, Scale AI, and former YC foundersBuild a massive, fast-growing business with billions in revenueAbout Handshake AIHuman data is the core infrastructure to AI advancement. Frontier AI labs currently improve model capabilities with various data-intensive post-training techniques. We believe that data spend for AI training will increase by 3-5x in the next few years and continue for much longer as models take on new domains. Handshake AI supports all of the frontier AI labs, working on their most complex data at the largest scale.We are building our India team to help accelerate the development of frontier models. This team is a critical, strategic investment for us - we have grown the team 3x in the past six months to help fuel our next phase of growth. India-based teammates will work hand-in-hand with US-based teams to scope, execute, and deliver critical human data projects to Frontier Labs and other customers.About the RoleWe’re hiring a Senior Software Engineer to build our Reinforcement Learning Environments (RLE) platform—the interactive systems where frontier AI models learn to complete real-world work.RLE environments simulate workflows (e.g., software engineering, finance, legal) with realistic tools, constraints, and feedback loops. The data generated powers training and evaluation for model quality, robustness, and task completion.This is a high-ownership role with direct impact on how models learn and how quickly new domains scale. What You’ll DoBuild and scale our reinforcement learning environments and the platforms behind themDrive architecture for scalable, reliable, extensible environment systems and data generation pipelinesPartner with Research, Product, and Ops to turn ambiguous needs into production systemsBuild modular, plug-and-play domains that integrate cleanly with training and evaluation loopsRaise the bar on reliability, observability, performance, and data quality What We’re Looking For7+ years building backend, distributed systems, or ML infrastructureProficiency with Node.js And ReactJS OR TypeScript, with deep knowledge of backend architectures.Strong command of relational databases (e.g., PostgreSQL), data modeling, system design, and distributed systems principles.Experience with cloud infrastructure (AWS, GCP), CI/CD pipelines, and operating production systems at scale.Strong applied AI experience is requiredFull-stack or backend-leaning engineers preferred. Nice to HaveExperience with RL training infrastructure, simulation systems, or evaluation platformsWorking in an operations-heavy, tech-enabled environmentExperience supporting applied ML or AI research teams What Success Looks LikeRLE becomes a trusted platform for training workflow-capable modelsNew domains launch quickly with high-quality dataSystems are reliable, scalable, and drive measurable model improvementsYou’ll Thrive Here If You:Are motivated by solving operational problems that have direct, measurable impact.Want to be part of a company shaping the future of AI through human data.Can navigate ambiguity, act with urgency, and keep multiple workstreams moving in parallel.Perks:Generous Equity Grant vested over 4 yearsHousing Bonus: 1.3 Lakhs spread throughout the first yearWell Defined Performance Bonus ranging between 10 - 100% of baseMedical Insurance CoverageFood credit for every in person day.   

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Shape the Future of AI At Labelbox, we're building the critical infrastructure that powers breakthrough AI models at leading research labs and enterprises. Since 2018, we've been pioneering data-centric approaches that are fundamental to AI development, and our work becomes even more essential as AI capabilities expand exponentially. About Labelbox We're the only company offering three integrated solutions for frontier AI development: Enterprise Platform & Tools: Advanced annotation tools, workflow automation, and quality control systems that enable teams to produce high-quality training data at scale Frontier Data Labeling Service: Specialized data labeling through Alignerr, leveraging subject matter experts for next-generation AI models Expert Marketplace: Connecting AI teams with highly skilled annotators and domain experts for flexible scaling Why Join Us High-Impact Environment: We operate like an early-stage startup, focusing on impact over process. You'll take on expanded responsibilities quickly, with career growth directly tied to your contributions. Technical Excellence: Work at the cutting edge of AI development, collaborating with industry leaders and shaping the future of artificial intelligence. Innovation at Speed: We celebrate those who take ownership, move fast, and deliver impact. Our environment rewards high agency and rapid execution. Continuous Growth: Every role requires continuous learning and evolution. You'll be surrounded by curious minds solving complex problems at the frontier of AI. Clear Ownership: You'll know exactly what you're responsible for and have the autonomy to execute. We empower people to drive results through clear ownership and metrics. Role Overview As an Applied Research Engineer at Labelbox, you’ll sit at the junction of advanced AI research and real product impact, with a focus on the data that makes modern agents work—browser interactions, SWE/code traces, GUI sessions, and multi-turn workflows. You’ll drive the data landscape required to advance capable, adaptable agents and help shape Labelbox’s strategy for collecting, synthesizing, and evaluating it. You will possess expertise in LLM agents and planning/execution loops, plus creativity in tackling problems across data design, interaction, and measurement. You’ll publish meaningful results, collaborate with customer researchers in frontier AI labs, and turn prototypes into reliable, scalable features. Your Impact Create frameworks and tools to construct, train, benchmark and evaluate autonomous agent capabilities. Design agent-focused data programs using supervised fine-tuning (SFT) and reinforcement learning (RL) methodologies. Develop data pipelines from diverse sources like code repositories, web browsers, and computer systems. Implement and adapt popular open-source agent libraries and benchmarks with proprietary datasets and models. Engage with research teams in frontier AI labs and the wider AI community to understand evolving agent data needs for frontier models and share best practices. Collaborate closely with frontier AI lab customers to understand requirements and guide model development. Publish research findings in academic journals, conferences, and blog posts. What You Bring Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or related field. At least 3 years of experience addressing sophisticated ML problems with successful delivery to customers. Experience building and training autonomous agents—tool use, structured outputs, multi-step planning—across browsers/GUI, codebases, and databases using SFT and RL. Constructed and evaluated agentic benchmarks (e.g. SWE-bench, WebArena, τ-bench, OSWorld) and reliability/efficiency suites (e.g. WABER).  Adept at interpreting research literature and quickly turning new ideas into prototypes. Deep understanding of frontier models (autoregressive, diffusion), post-training (SFT, RLVR, RLAIF, RLHF, et al.), and their human data requirements. Proficient in Python, data science libraries and deep learning frameworks (e.g., PyTorch, JAX, TensorFlow). Strong analytical and problem-solving abilities in ambiguous situations. Excellent communication skills. Track record of publications in top-tier AI/ML venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, etc.). Labelbox Applied Research At Labelbox Applied Research, we're committed to pushing the boundaries of AI and data-centric machine learning, with a particular focus on advanced human-AI interaction techniques. We believe that high-quality human data and sophisticated human feedback integration methods are key to unlocking the next generation of AI capabilities. Our research team works at the intersection of machine learning, human-computer interaction, and AI ethics to develop innovative solutions that can be practically applied in real-world scenarios. We foster an environment of intellectual curiosity, collaboration, and innovation. We encourage our researchers to explore new ideas, engage in open discussions, and contribute to the wider AI community through publications and conference presentations. Our goal is to be at the forefront of human-centric AI development, setting new standards for how AI systems learn from and interact with humans.Labelbox strives to ensure pay parity across the organization and discuss compensation transparently.  The expected annual base salary range for United States-based candidates is below. This range is not inclusive of any potential equity packages or additional benefits. Exact compensation varies based on a variety of factors, including skills and competencies, experience, and geographical location.Annual base salary range$250,000—$300,000 USDLife at Labelbox Location: Join our dedicated tech hubs in San Francisco or Wrocław, Poland Work Style: Hybrid model with 2 days per week in office, combining collaboration and flexibility Environment: Fast-paced and high-intensity, perfect for ambitious individuals who thrive on ownership and quick decision-making Growth: Career advancement opportunities directly tied to your impact Vision: Be part of building the foundation for humanity's most transformative technology Our Vision We believe data will remain crucial in achieving artificial general intelligence. As AI models become more sophisticated, the need for high-quality, specialized training data will only grow. Join us in developing new products and services that enable the next generation of AI breakthroughs. Labelbox is backed by leading investors including SoftBank, Andreessen Horowitz, B Capital, Gradient Ventures, Databricks Ventures, and Kleiner Perkins. Our customers include Fortune 500 enterprises and leading AI labs. Your Personal Data Privacy: Any personal information you provide Labelbox as a part of your application will be processed in accordance with Labelbox’s Job Applicant Privacy notice. Any emails from Labelbox team members will originate from a @labelbox.com email address. If you encounter anything that raises suspicions during your interactions, we encourage you to exercise caution and suspend or discontinue communications.

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Shape the Future of AI At Labelbox, we're building the critical infrastructure that powers breakthrough AI models at leading research labs and enterprises. Since 2018, we've been pioneering data-centric approaches that are fundamental to AI development, and our work becomes even more essential as AI capabilities expand exponentially. About Labelbox We're the only company offering three integrated solutions for frontier AI development: Enterprise Platform & Tools: Advanced annotation tools, workflow automation, and quality control systems that enable teams to produce high-quality training data at scale Frontier Data Labeling Service: Specialized data labeling through Alignerr, leveraging subject matter experts for next-generation AI models Expert Marketplace: Connecting AI teams with highly skilled annotators and domain experts for flexible scaling Why Join Us High-Impact Environment: We operate like an early-stage startup, focusing on impact over process. You'll take on expanded responsibilities quickly, with career growth directly tied to your contributions. Technical Excellence: Work at the cutting edge of AI development, collaborating with industry leaders and shaping the future of artificial intelligence. Innovation at Speed: We celebrate those who take ownership, move fast, and deliver impact. Our environment rewards high agency and rapid execution. Continuous Growth: Every role requires continuous learning and evolution. You'll be surrounded by curious minds solving complex problems at the frontier of AI. Clear Ownership: You'll know exactly what you're responsible for and have the autonomy to execute. We empower people to drive results through clear ownership and metrics. Role Overview As an Applied Research Engineer at Labelbox, you’ll sit at the junction of advanced AI research and real product impact, with a focus on the data that makes modern agents work—browser interactions, SWE/code traces, GUI sessions, and multi-turn workflows. You’ll drive the data landscape required to advance capable, adaptable agents and help shape Labelbox’s strategy for collecting, synthesizing, and evaluating it. You will possess expertise in LLM agents and planning/execution loops, plus creativity in tackling problems across data design, interaction, and measurement. You’ll publish meaningful results, collaborate with customer researchers in frontier AI labs, and turn prototypes into reliable, scalable features. Your Impact Create frameworks and tools to construct, train, benchmark and evaluate autonomous agent capabilities. Design agent-focused data programs using supervised fine-tuning (SFT) and reinforcement learning (RL) methodologies. Develop data pipelines from diverse sources like code repositories, web browsers, and computer systems. Implement and adapt popular open-source agent libraries and benchmarks with proprietary datasets and models. Engage with research teams in frontier AI labs and the wider AI community to understand evolving agent data needs for frontier models and share best practices. Collaborate closely with frontier AI lab customers to understand requirements and guide model development. Publish research findings in academic journals, conferences, and blog posts. What You Bring Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or related field. At least 3 years of experience addressing sophisticated ML problems with successful delivery to customers. Experience building and training autonomous agents—tool use, structured outputs, multi-step planning—across browsers/GUI, codebases, and databases using SFT and RL. Constructed and evaluated agentic benchmarks (e.g. SWE-bench, WebArena, τ-bench, OSWorld) and reliability/efficiency suites (e.g. WABER).  Adept at interpreting research literature and quickly turning new ideas into prototypes. Deep understanding of frontier models (autoregressive, diffusion), post-training (SFT, RLVR, RLAIF, RLHF, et al.), and their human data requirements. Proficient in Python, data science libraries and deep learning frameworks (e.g., PyTorch, JAX, TensorFlow). Strong analytical and problem-solving abilities in ambiguous situations. Excellent communication skills. Track record of publications in top-tier AI/ML venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, etc.). Labelbox Applied Research At Labelbox Applied Research, we're committed to pushing the boundaries of AI and data-centric machine learning, with a particular focus on advanced human-AI interaction techniques. We believe that high-quality human data and sophisticated human feedback integration methods are key to unlocking the next generation of AI capabilities. Our research team works at the intersection of machine learning, human-computer interaction, and AI ethics to develop innovative solutions that can be practically applied in real-world scenarios. We foster an environment of intellectual curiosity, collaboration, and innovation. We encourage our researchers to explore new ideas, engage in open discussions, and contribute to the wider AI community through publications and conference presentations. Our goal is to be at the forefront of human-centric AI development, setting new standards for how AI systems learn from and interact with humans.Labelbox strives to ensure pay parity across the organization and discuss compensation transparently.  The expected annual base salary range for United States-based candidates is below. This range is not inclusive of any potential equity packages or additional benefits. Exact compensation varies based on a variety of factors, including skills and competencies, experience, and geographical location.Annual base salary range$250,000—$300,000 USDLife at Labelbox Location: Join our dedicated tech hubs in San Francisco or Wrocław, Poland Work Style: Hybrid model with 2 days per week in office, combining collaboration and flexibility Environment: Fast-paced and high-intensity, perfect for ambitious individuals who thrive on ownership and quick decision-making Growth: Career advancement opportunities directly tied to your impact Vision: Be part of building the foundation for humanity's most transformative technology Our Vision We believe data will remain crucial in achieving artificial general intelligence. As AI models become more sophisticated, the need for high-quality, specialized training data will only grow. Join us in developing new products and services that enable the next generation of AI breakthroughs. Labelbox is backed by leading investors including SoftBank, Andreessen Horowitz, B Capital, Gradient Ventures, Databricks Ventures, and Kleiner Perkins. Our customers include Fortune 500 enterprises and leading AI labs. Your Personal Data Privacy: Any personal information you provide Labelbox as a part of your application will be processed in accordance with Labelbox’s Job Applicant Privacy notice. Any emails from Labelbox team members will originate from a @labelbox.com email address. If you encounter anything that raises suspicions during your interactions, we encourage you to exercise caution and suspend or discontinue communications.

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Shape the Future of AI At Labelbox, we're building the critical infrastructure that powers breakthrough AI models at leading research labs and enterprises. Since 2018, we've been pioneering data-centric approaches that are fundamental to AI development, and our work becomes even more essential as AI capabilities expand exponentially. About Labelbox We're the only company offering three integrated solutions for frontier AI development: Enterprise Platform & Tools: Advanced annotation tools, workflow automation, and quality control systems that enable teams to produce high-quality training data at scale Frontier Data Labeling Service: Specialized data labeling through Alignerr, leveraging subject matter experts for next-generation AI models Expert Marketplace: Connecting AI teams with highly skilled annotators and domain experts for flexible scaling Why Join Us High-Impact Environment: We operate like an early-stage startup, focusing on impact over process. You'll take on expanded responsibilities quickly, with career growth directly tied to your contributions. Technical Excellence: Work at the cutting edge of AI development, collaborating with industry leaders and shaping the future of artificial intelligence. Innovation at Speed: We celebrate those who take ownership, move fast, and deliver impact. Our environment rewards high agency and rapid execution. Continuous Growth: Every role requires continuous learning and evolution. You'll be surrounded by curious minds solving complex problems at the frontier of AI. Clear Ownership: You'll know exactly what you're responsible for and have the autonomy to execute. We empower people to drive results through clear ownership and metrics. Role Overview As an Applied Research Engineer at Labelbox, you’ll sit at the junction of advanced AI research and real product impact, with a focus on the data that makes modern agents work—browser interactions, SWE/code traces, GUI sessions, and multi-turn workflows. You’ll drive the data landscape required to advance capable, adaptable agents and help shape Labelbox’s strategy for collecting, synthesizing, and evaluating it. You will possess expertise in LLM agents and planning/execution loops, plus creativity in tackling problems across data design, interaction, and measurement. You’ll publish meaningful results, collaborate with customer researchers in frontier AI labs, and turn prototypes into reliable, scalable features. Your Impact Create frameworks and tools to construct, train, benchmark and evaluate autonomous agent capabilities. Design agent-focused data programs using supervised fine-tuning (SFT) and reinforcement learning (RL) methodologies. Develop data pipelines from diverse sources like code repositories, web browsers, and computer systems. Implement and adapt popular open-source agent libraries and benchmarks with proprietary datasets and models. Engage with research teams in frontier AI labs and the wider AI community to understand evolving agent data needs for frontier models and share best practices. Collaborate closely with frontier AI lab customers to understand requirements and guide model development. Publish research findings in academic journals, conferences, and blog posts. What You Bring Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or related field. At least 3 years of experience addressing sophisticated ML problems with successful delivery to customers. Experience building and training autonomous agents—tool use, structured outputs, multi-step planning—across browsers/GUI, codebases, and databases using SFT and RL. Constructed and evaluated agentic benchmarks (e.g. SWE-bench, WebArena, τ-bench, OSWorld) and reliability/efficiency suites (e.g. WABER).  Adept at interpreting research literature and quickly turning new ideas into prototypes. Deep understanding of frontier models (autoregressive, diffusion), post-training (SFT, RLVR, RLAIF, RLHF, et al.), and their human data requirements. Proficient in Python, data science libraries and deep learning frameworks (e.g., PyTorch, JAX, TensorFlow). Strong analytical and problem-solving abilities in ambiguous situations. Excellent communication skills. Track record of publications in top-tier AI/ML venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, etc.). Labelbox Applied Research At Labelbox Applied Research, we're committed to pushing the boundaries of AI and data-centric machine learning, with a particular focus on advanced human-AI interaction techniques. We believe that high-quality human data and sophisticated human feedback integration methods are key to unlocking the next generation of AI capabilities. Our research team works at the intersection of machine learning, human-computer interaction, and AI ethics to develop innovative solutions that can be practically applied in real-world scenarios. We foster an environment of intellectual curiosity, collaboration, and innovation. We encourage our researchers to explore new ideas, engage in open discussions, and contribute to the wider AI community through publications and conference presentations. Our goal is to be at the forefront of human-centric AI development, setting new standards for how AI systems learn from and interact with humans.Labelbox strives to ensure pay parity across the organization and discuss compensation transparently.  The expected annual base salary range for United States-based candidates is below. This range is not inclusive of any potential equity packages or additional benefits. Exact compensation varies based on a variety of factors, including skills and competencies, experience, and geographical location.Annual base salary range$250,000—$300,000 USDLife at Labelbox Location: Join our dedicated tech hubs in San Francisco or Wrocław, Poland Work Style: Hybrid model with 2 days per week in office, combining collaboration and flexibility Environment: Fast-paced and high-intensity, perfect for ambitious individuals who thrive on ownership and quick decision-making Growth: Career advancement opportunities directly tied to your impact Vision: Be part of building the foundation for humanity's most transformative technology Our Vision We believe data will remain crucial in achieving artificial general intelligence. As AI models become more sophisticated, the need for high-quality, specialized training data will only grow. Join us in developing new products and services that enable the next generation of AI breakthroughs. Labelbox is backed by leading investors including SoftBank, Andreessen Horowitz, B Capital, Gradient Ventures, Databricks Ventures, and Kleiner Perkins. Our customers include Fortune 500 enterprises and leading AI labs. Your Personal Data Privacy: Any personal information you provide Labelbox as a part of your application will be processed in accordance with Labelbox’s Job Applicant Privacy notice. Any emails from Labelbox team members will originate from a @labelbox.com email address. If you encounter anything that raises suspicions during your interactions, we encourage you to exercise caution and suspend or discontinue communications.

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Role Overview Scale’s rapidly growing Global Public Sector team is focused on using AI to address critical challenges facing the public sector around the world. Our core work consists of: Creating custom AI applications that will impact millions of citizens Generating high-quality training data for national LLMs Upskilling and advisory services to spread the impact of AI As a Production AI Ops Lead, you will design and develop the production lifecycle of full-stack AI applications, while supporting end-to-end system reliability, real-time inference observability, sovereign data orchestration, high-security software integration, and the resilient cloud infrastructure required for our international government partners. At Scale, we’re not just building AI solutions—we’re enabling the public sector to transform their operations and better serve citizens through cutting-edge technology. If you’re ready to shape the future of AI in the public sector and be a founding member of our team, we’d love to hear from you. You will: Own the production outcome: Take full accountability for the long-term performance and reliability of AI use cases deployed across international government agencies. Ensure Full-Stack integrity: Oversee the end-to-end health of the platform, ensuring seamless integration between the AI core and all full-stack components, from APIs to UI, to maintain a responsive and production-ready environment. Scale the feedback loop: Build automated systems to monitor model performance and data drift across geographically dispersed environments, ensuring the right levels of reliability. Navigate global compliance: Manage the technical lifecycle within diverse regulatory frameworks. Incident command: Lead the response for production issues in mission-critical environments, ensuring rapid resolution and building the guardrails to prevent them from happening again. Bridge the gap: Translate deep technical performance metrics into clear insights for senior international government officials. Drive product evolution: Partner with our Engineering and ML teams to ensure the lessons learned in the field directly influence the technical architecture and decisions of future use cases. Ideally, you have: Experience: 6+ years in a high-impact technical role (SRE, FDE or MLOps) with experience in the public sector. Global perspective: Familiarity with international government security standards and the complexities of deploying sovereign AI. System architecture proficiency: Proven experience maintaining production-grade applications with a deep understanding of the full request lifecycle-connecting frontend/API layers to the backend and AI core. Modern AI Stack expertise: Proficiency in coding and the modern AI infrastructure, including Kubernetes, vector databases, agentic development, and LLM observability tools. Ownership: You treat every production deployment as your own. You race toward solving hard problems before the customer even sees them. Reliability: You understand that in the public sector, a model failure may be a risk to public safety or privacy. Customer communication: The ability to explain to a high-ranking official why the performance of the system has degraded and how we are fixing it. PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.  We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision.  PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

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Role Overview Scale’s rapidly growing Global Public Sector team is focused on using AI to address critical challenges facing the public sector around the world. Our core work consists of: Creating custom AI applications that will impact millions of citizens Generating high-quality training data for national LLMs Upskilling and advisory services to spread the impact of AI As a Production AI Ops Lead, you will design and develop the production lifecycle of full-stack AI applications, while supporting end-to-end system reliability, real-time inference observability, sovereign data orchestration, high-security software integration, and the resilient cloud infrastructure required for our international government partners. At Scale, we’re not just building AI solutions—we’re enabling the public sector to transform their operations and better serve citizens through cutting-edge technology. If you’re ready to shape the future of AI in the public sector and be a founding member of our team, we’d love to hear from you. You will: Own the production outcome: Take full accountability for the long-term performance and reliability of AI use cases deployed across international government agencies. Ensure Full-Stack integrity: Oversee the end-to-end health of the platform, ensuring seamless integration between the AI core and all full-stack components, from APIs to UI, to maintain a responsive and production-ready environment. Scale the feedback loop: Build automated systems to monitor model performance and data drift across geographically dispersed environments, ensuring the right levels of reliability. Navigate global compliance: Manage the technical lifecycle within diverse regulatory frameworks. Incident command: Lead the response for production issues in mission-critical environments, ensuring rapid resolution and building the guardrails to prevent them from happening again. Bridge the gap: Translate deep technical performance metrics into clear insights for senior international government officials. Drive product evolution: Partner with our Engineering and ML teams to ensure the lessons learned in the field directly influence the technical architecture and decisions of future use cases. Ideally, you have: Experience: 6+ years in a high-impact technical role (SRE, FDE or MLOps) with experience in the public sector. Global perspective: Familiarity with international government security standards and the complexities of deploying sovereign AI. System architecture proficiency: Proven experience maintaining production-grade applications with a deep understanding of the full request lifecycle-connecting frontend/API layers to the backend and AI core. Modern AI Stack expertise: Proficiency in coding and the modern AI infrastructure, including Kubernetes, vector databases, agentic development, and LLM observability tools. Ownership: You treat every production deployment as your own. You race toward solving hard problems before the customer even sees them. Reliability: You understand that in the public sector, a model failure may be a risk to public safety or privacy. Customer communication: The ability to explain to a high-ranking official why the performance of the system has degraded and how we are fixing it. PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.  We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision.  PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

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ABOUT xAI xAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates.ABOUT THE ROLE: We are seeking a dedicated AI Healthcare and Administration Data Specialist to enhance xAI’s AI models by providing high-quality data annotations and inputs tailored to healthcare and administration contexts. In this role, you will leverage your expertise in patient care coordination, medical billing, administrative workflows, and healthcare operations to support the training of AI systems. You will collaborate with technical teams to refine annotation tools and curate impactful data, ensuring our models effectively capture real-world healthcare and administrative dynamics. This role requires adaptability, strong analytical skills, and a passion for driving innovation in a fast-paced environment. RESPONSIBILITIES: Utilize proprietary software to provide accurate input and labels for healthcare and administration projects, ensuring high-quality data for AI model training. Deliver curated, high-quality data for scenarios involving patient care coordination, medical billing, administrative workflows, and healthcare operations. Collaborate with technical staff to support the training of new AI tasks and contribute to the development of innovative technologies. Assist in designing and improving efficient annotation tools tailored for healthcare and administration data. Select and analyze complex problems in healthcare and administration fields aligned with your expertise to enhance AI model performance. Interpret, analyze, and execute tasks based on evolving instructions, maintaining precision and adaptability. BASIC QUALIFICATIONS: Professional experience in healthcare administration or related fields (e.g., medical and health services manager, medical secretary, or administrative assistant). Proficiency in reading and writing informal and professional English. Strong communication, interpersonal, analytical, and organizational skills. Excellent reading comprehension and ability to exercise autonomous judgment with limited data. Passion for technological advancements and innovation in healthcare and administration processes. PREFERRED SKILLS AND EXPERIENCE: Relevant certification or training (e.g., Certified Medical Manager, Certified Professional in Healthcare Management, or similar administrative certification). Experience mentoring or training others in healthcare administration or operational practices. Comfort with recording audio or video sessions for data collection. Familiarity with AI or data annotation workflows in a technical setting. LOCATION AND OTHER EXPECTATIONS: Tutor roles may be offered as full-time, part-time, or contractor positions, depending on role needs and candidate fit. For contractor positions, hours will vary widely based on project scope and contractor availability, with no fixed commitments required.  On average most projects may involve at least 10 hours per week to achieve deliverables effectively though this is not a fixed commitment and depends on the scope of work. Contractors have full flexibility to set their own hours and determine the exact amount of time needed to complete deliverables.  Tutor roles may be performed remotely from any location worldwide, subject to legal eligibility, time-zone compatibility, and role specific needs. For US based candidates, please note we are unable to hire in the states of Wyoming and Illinois at this time. We are unable to provide visa sponsorship. For those who will be working from a personal device, your computer must be a Chromebook, Mac with MacOS 11.0 or later, or Windows 10 or later. COMPENSATION AND BENEFITS: US based candidates: $45/hour - $100/hour depending on factors including relevant experience, skills, education, geographic location, and qualifications. International candidates: Information will be provided to you during the recruitment process. Benefits vary based on employment type, location and jurisdiction. Benefits for eligible U.S. based positions include health insurance, 401(k) plan, and paid sick leave. Specific details and role specific information will be provided to you during the interview process.xAI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice.

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About Loop Loop is the data platform for the global supply chain. Logistics runs on messy, unstructured data—trapped in PDFs, emails, and legacy systems. We use AI to structure this chaos, creating a "source of truth" that automates payments and audits for the Fortune 100. We are building the financial nervous system for a $100 trillion physical economy. Our technology ensures freight moves efficiently and carriers get paid instantly. Backed by Founders Fund, Index Ventures and 8VC, we are scaling rapidly. We are looking for engineers ready to deploy production AI that powers the physical economy. About the New Grad Program Most AI stays in the browser. Ours moves atoms. You aren't just building features; you are building the autonomous brain for the Fortune 100’s global supply chain. This program is designed to compress 3 years of learning into 1 year by throwing you into the deep end of production AI systems on Day 1. Instead of sandboxed projects, you get to solve real problems and impact customers directly. This program demands intense investment, but by the end, you will perform as a strong entry-level engineer jumpstarting your career. The Schedule: Week 1 (Onboarding): Deep dive into tools and domain. You will ship code to production on Day 1 and fully grasp our dev loop by Friday. Months 1-3 (Velocity): You will deliver 3 entry-level projects with increasing ambiguity. By the end of Month 3, you are expected to operate as a fully independent engineer. Months 4-9 (The Rotation): You will rotate onto a different high-impact team to expand your surface area. Tracks include: Platform: AI infrastructure and Engineering Systems. Core Product: Audit, Billing, and Payments logic. Commercial: Revenue Activation and Forward Deployed Engineering. Special Projects: Partnering directly with the CEO/CTO and other execs Month 9+ (Graduation): You should demonstrate Mid-Level Engineer performance and will be considered for immediate promotion. About You We're not just looking for strong academic performers. We're looking for people who are genuinely driven to build things and go deep on hard problems. If the following resonates, you belong here: You go above and beyond. You have a repo, a side hustle, or a project you built just because you are curious. You’re self-directed and don't need an assignment to start coding. You have a bias towards action. You prefer to ship, break, fix, and apologize rather than wait for a committee decision. You are drawn to hard problems. You want problems that are more than one prompt away from a solution. You get absorbed in mastering your craft. Whether it’s climbing the Esports ladder, acing a math competition, winning a hackathon, or debugging a complex issue, you know what it feels like to lose track of time working on something you care about. Responsibilities Ship critical infrastructure. Manage real-world logistics and financial data for the largest enterprise in the world..  Own the why. Build deep context through customer calls, and understand the Loop’s value to our customers. You push back on requirements if you see a better, faster way to solve the customer’s problem. Full-stack proficiency. Work across system boundaries, from frontend UX to LLM agents, database schema and event infrastructures. Leverage AI tools to handle the 90% boilerplate, so you can focus the highest leverage 10%: quality, architecture, product taste. Raise the velocity bar. You will constantly optimize our dev loops, refactor legacy patterns, automate your own workflows and fix broken processes. Qualifications Graduating with a BS or higher in STEM fields; available to start full-time in 2026. Working in person in the SF or Chicago office 4 days a week. Proficiency with modern techstack. You can deliver a modern web app in hours not in days.. Unblocking yourself. You thrive in ambiguity. Despite the chaos, you deliver high quality products and business impact. AI Literate. You have strong intuition on how LLM works: where they excel and where they generate slop. You live and breathe AI native tools (Cursor, Codex, Claude Code etc.) Compensation $125,000 annual base pay for Chicago Benefits & Perks This role is eligible for Loop’s health insurance, dental insurance, vision insurance, 401(k) plan, paid time off, paid holidays, parental leave, and other company-sponsored benefits. #LI-LOOP

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About Loop Loop is the data platform for the global supply chain. Logistics runs on messy, unstructured data—trapped in PDFs, emails, and legacy systems. We use AI to structure this chaos, creating a "source of truth" that automates payments and audits for the Fortune 100. We are building the financial nervous system for a $100 trillion physical economy. Our technology ensures freight moves efficiently and carriers get paid instantly. Backed by Founders Fund, Index Ventures and 8VC, we are scaling rapidly. We are looking for engineers ready to deploy production AI that powers the physical economy. About the New Grad Program Most AI stays in the browser. Ours moves atoms. You aren't just building features; you are building the autonomous brain for the Fortune 100’s global supply chain. This program is designed to compress 3 years of learning into 1 year by throwing you into the deep end of production AI systems on Day 1. Instead of sandboxed projects, you get to solve real problems and impact customers directly. This program demands intense investment, but by the end, you will perform as a strong entry-level engineer jumpstarting your career. The Schedule: Week 1 (Onboarding): Deep dive into tools and domain. You will ship code to production on Day 1 and fully grasp our dev loop by Friday. Months 1-3 (Velocity): You will deliver 3 entry-level projects with increasing ambiguity. By the end of Month 3, you are expected to operate as a fully independent engineer. Months 4-9 (The Rotation): You will rotate onto a different high-impact team to expand your surface area. Tracks include: Platform: AI infrastructure and Engineering Systems. Core Product: Audit, Billing, and Payments logic. Commercial: Revenue Activation and Forward Deployed Engineering. Special Projects: Partnering directly with the CEO/CTO and other execs Month 9+ (Graduation): You should demonstrate Mid-Level Engineer performance and will be considered for immediate promotion. About You We're not just looking for strong academic performers. We're looking for people who are genuinely driven to build things and go deep on hard problems. If the following resonates, you belong here: You go above and beyond. You have a repo, a side hustle, or a project you built just because you are curious. You’re self-directed and don't need an assignment to start coding. You have a bias towards action. You prefer to ship, break, fix, and apologize rather than wait for a committee decision. You are drawn to hard problems. You want problems that are more than one prompt away from a solution. You get absorbed in mastering your craft. Whether it’s climbing the Esports ladder, acing a math competition, winning a hackathon, or debugging a complex issue, you know what it feels like to lose track of time working on something you care about. Responsibilities Ship critical infrastructure. Manage real-world logistics and financial data for the largest enterprise in the world..  Own the why. Build deep context through customer calls, and understand the Loop’s value to our customers. You push back on requirements if you see a better, faster way to solve the customer’s problem. Full-stack proficiency. Work across system boundaries, from frontend UX to LLM agents, database schema and event infrastructures. Leverage AI tools to handle the 90% boilerplate, so you can focus the highest leverage 10%: quality, architecture, product taste. Raise the velocity bar. You will constantly optimize our dev loops, refactor legacy patterns, automate your own workflows and fix broken processes. Qualifications Graduating with a BS or higher in STEM fields; available to start full-time in 2026. Working in person in the SF or Chicago office 4 days a week. Proficiency with modern techstack. You can deliver a modern web app in hours not in days.. Unblocking yourself. You thrive in ambiguity. Despite the chaos, you deliver high quality products and business impact. AI Literate. You have strong intuition on how LLM works: where they excel and where they generate slop. You live and breathe AI native tools (Cursor, Codex, Claude Code etc.) Compensation $125,000 annual base pay for Chicago Benefits & Perks This role is eligible for Loop’s health insurance, dental insurance, vision insurance, 401(k) plan, paid time off, paid holidays, parental leave, and other company-sponsored benefits. #LI-LOOP