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About Snorkel At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data. We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes between 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!About Snorkel We’re on a mission to democratize AI by building the definitive AI data development platform. The AI landscape has gone through incredible change between 2016, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! As an Applied AI Engineer, you’ll research and utilize state-of-the-art Gen AI and machine learning (ML) techniques to successfully deliver solutions to our customers. You will work directly with our customers to understand their business and technical needs and design and deliver AI solutions to solve them - either by leveraging Snorkel Flow or developing custom approaches when needed. You will also help define Snorkel’s Applied AI tooling by translating repeatable real-world challenges into reusable solution recipes, workflows, best practices, and platform-level capabilities that become part of Snorkel Flow’s next generation of AI tooling. We move fast and are constantly prototyping and innovating new ways to deliver value to our customers. This position is ideal for someone who enjoys solving complex problems, bridging the gap between AI technology and business value, working directly with customers, keeping up-to date with AI research, and standardizing bespoke solutions into internal recipes and staying naturally curious about the infrastructure that underpin the Applied AI stack end-to-end. Main Responsibilities Partner with customers to build and deploy impactful Gen AI and machine learning solutions, from use case scoping and data exploration to model development and deployment. This may involve leveraging Snorkel Flow or designing custom approaches using state-of-the-art tools, with the goal of delivering real business value and informing the evolution of the Snorkel platform. Develop and implement state of the art AI systems such as retrieval-augmented generation (RAG), fine-tuning pipelines, prompt engineering recipes and agentic workflows. Create augmented real-world datasets and comprehensive evaluation workflows to ensure model reliability, transparency, and stakeholder trust. A data- and evaluation-first mindset is essential for success in this role. Forge and manage relationships with our customers’ leadership and stakeholders to ensure successful development and deployment of AI projects with Snorkel Flow. Collaborate closely with pre-sales Solutions and Product teams to map customer needs to existing capabilities, prioritize roadmap gaps, and guide successful project setup. Work with other Applied AI Engineers to standardize solutions and contribute to internal tooling and best practices. Lead stakeholder education on quantitative capabilities, helping them to understand the strengths and weaknesses of different approaches and what problems are best-suited for Snorkel AI. Serve as the voice of our customers for new AI paradigms, data science workflows, and share customer feedback to product teams. Conduct one-to-few and one-to-many enablement workshops to transfer knowledge to customers considering or already using Snorkel AI. Annual travel up to 25%. Preferred Qualifications B.S. degree in a quantitative field such as Computer Science, Engineering, Mathematics, Statistics, or comparable degree/experience. 3+ years of customer-facing experience in the design and implementation of AI/ML solutions. Proficiency in Python, including strong grounding in software engineering fundamentals (e.g., modular design, testing, profiling, packaging) and experience with modern Python constructs and libraries for type validation and typed data modeling (e.g., pydantic), building type-safe systems (e.g., mypy), testing (e.g., pytest), packaging and environment configuration (e.g., poetry), API and service frameworks (e.g., FastAPI), serialization and structured data handling (e.g., msgspec), and orchestration tooling relevant to ML deployment (e.g., Ray, Airflow). Expertise across the Applied AI stack, spanning classical ML libraries (e.g., scikit-learn), deep learning frameworks (e.g., PyTorch), foundation-model ecosystems (e.g., Hugging Face Transformers), vector/embedding tooling (e.g., FAISS), data processing frameworks (e.g., pandas, Spark), retrieval/RAG tooling (e.g., Chroma, Weaviate), synthetic dataset curation, evaluation workflows, and LLM orchestration, workflow, agent authoring tools (e.g., LlamaIndex, LangGraph, CrewAI). Experience leading strategic, customer-facing initiatives and collaborating with business stakeholders to ensure ML solutions drive successful business outcomes, with a strong focus on teaching and enablement. Outstanding presentation skills to technical and executive audiences, whether impromptu on a whiteboard or using presentations and demos. Ability to work in a fast-paced environment and balance priorities across multiple projects at once. Compensation range for Tier 1 locations of San Francisco Bay Area $172K - $300K OTE. All offers also include equity in the form of employee stock options. Our compensation ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Locations Redwood City, CA - Hybrid; San Francisco, CA - Hybrid - US; New York, NY - Hybrid #LI-CG1Salary Range $172,000—$300,000 USDBe Your Best at Snorkel Joining Snorkel AI means becoming part of a company that has market proven solutions, robust funding, and is scaling rapidly—offering a unique combination of stability and the excitement of high growth. As a member of our team, you’ll have meaningful opportunities to shape priorities and initiatives, influence key strategic decisions, and directly impact our ongoing success. Whether you’re looking to deepen your technical expertise, explore leadership opportunities, or learn new skills across multiple functions, you’re fully supported in building your career in an environment designed for growth, learning, and shared success. Snorkel AI is proud to be an Equal Employment Opportunity employer and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. Snorkel AI embraces diversity and provides equal employment opportunities to all employees and applicants for employment. Snorkel AI prohibits discrimination and harassment of any type on the basis of race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local law. All employment is decided on the basis of qualifications, performance, merit, and business need. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

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Why HarveyAt Harvey, we’re transforming how legal and professional services operate — not incrementally, but end-to-end. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come.This is a rare chance to help build a generational company at a true inflection point. With 1000+ customers in 58+ countries, strong product-market fit, and world-class investor support, we’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched.Our team is sharp, motivated, and deeply committed to the mission. We move fast, operate with intensity, and take real ownership of the problems we tackle — from early thinking to long-term outcomes. We stay close to our customers — from leadership to engineers — and work together to solve real problems with urgency and care. If you thrive in ambiguity, push for excellence, and want to help shape the future of work alongside others who raise the bar, we invite you to build with us.At Harvey, the future of professional services is being written today — and we’re just getting started.Role OverviewHarvey’s products all depend on a shared AI foundation: the model layer and agent infrastructure that determine the quality of work our agents deliver. Legal is one of the hardest domains for AI: documents run to hundreds of pages, matters can span millions of files, and there is zero margin for error on accuracy.The AI Platform team builds the foundation that every product and agent team at Harvey builds upon. This team is early and there’s a lot to build: model routing, agent architecture, context management, evals. Your work here sets the ceiling for what Harvey’s AI can do.Representative ProjectsContext Engineering & Agent Infrastructure. Build the platform-level systems for context management, session state, and memory that all of Harvey’s agents and products rely on.Model Integration & Routing. Own the infrastructure that lets Harvey onboard new foundation models fast and route to the right one for every task - a capability every product team depends on.Evaluation Infrastructure. Build the shared eval tooling and frameworks that let every team across Harvey measure and improve AI quality systematically.Shared Abstractions. Create the SDKs, platform primitives, and developer tooling that make it dramatically easier for product teams to ship AI-powered features.What You’ll DoDesign and build abstractions and platform-level systems that improve all of Harvey’s agentic products.Own infrastructure for model integration, routing, and evaluation that helps Harvey choose and deploy the right foundation model for any given context.Build evaluation frameworks and tooling that let every team across Harvey iterate on AI quality effectively.Partner closely with product engineering teams, PMs, and design to launch cutting-edge AI products.Evaluate, prototype, and integrate the latest advancements in AI and agentic systems as they emerge.What You Have5+ years of experience building backend systems, with at least 1+ year focused on AI/ML engineering. Staff candidates will typically have 8+ years and a track record of technical leadership across teams.Experience building and shipping multi-model or multi-provider AI systems in production.Familiarity with context management, session state, or memory systems in AI or distributed systems. You’ve thought about what the model sees and why it matters.A track record of building internal platforms, SDKs, or shared infrastructure that other engineering teams actually adopted - and an understanding of why developer experience matters as much as raw capability.Strong judgment about abstractions. Opinionated about good design but pragmatic about shipping incrementally.Excitement about agentic AI and the infrastructure challenges of making autonomous systems reliable when the stakes are real.A bias toward full ownership: you navigate ambiguity well and don’t wait for a roadmap to start solving problems.Bonus: experience building evaluation frameworks, working with agent/function-calling architectures, familiarity with legal or other high-stakes professional services domains, or time at early-stage or hyper-growth startups where the underlying technology changes regularly.Compensation$220,000 - $300,000Please find our CA applicant privacy notice here.Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai

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About the TeamThe Future of Computing Research team is an Applied Research team within the Consumer Devices group focused on developing new methods and models to support our vision for the future of computing as we advance forward in our mission of building AGI that benefits all of humanity. About the RoleAs a Research Engineer/Scientist on the Future of Computing Research team, you will work together with both the best ML researchers in the world and the greatest design talent of our generation to push the frontier of model capabilities.This role is based in San Francisco, CA. We follow a hybrid model with 4 days a week in the office and offer relocation assistance to new employees. In this role you will:Train and evaluate SoTA models along axis that are important to our vision for future devices.Run through the necessary walls to take nascent research capabilities and turn them into capabilities we can build on top of.Help define how software works for decades to come.You might thrive in this role if you:Have 5+ years of relevant work experience.Have a research background in utilizing and training language models to generate UI, and developing recipes to evaluate the quality / applicability of UI generated.Love exposure to a bit of everything – we’re collaborators with a hugely diverse set of research.Do rigorous science (rather than vibes based). We need confidence in the experiments we run to move quickly.Have already spent time in the weeds teaching models to speak and perceive.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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Why HarveyAt Harvey, we’re transforming how legal and professional services operate — not incrementally, but end-to-end. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come.This is a rare chance to help build a generational company at a true inflection point. With 1000+ customers in 58+ countries, strong product-market fit, and world-class investor support, we’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched.Our team is sharp, motivated, and deeply committed to the mission. We move fast, operate with intensity, and take real ownership of the problems we tackle — from early thinking to long-term outcomes. We stay close to our customers — from leadership to engineers — and work together to solve real problems with urgency and care. If you thrive in ambiguity, push for excellence, and want to help shape the future of work alongside others who raise the bar, we invite you to build with us.At Harvey, the future of professional services is being written today — and we’re just getting started.Role OverviewHarvey’s products all depend on a shared AI foundation: the model layer and agent infrastructure that determine the quality of work our agents deliver. Legal is one of the hardest domains for AI: documents run to hundreds of pages, matters can span millions of files, and there is zero margin for error on accuracy.The AI Platform team builds the foundation that every product and agent team at Harvey builds upon. This team is early and there’s a lot to build: model routing, agent architecture, context management, evals. Your work here sets the ceiling for what Harvey’s AI can do.Representative ProjectsContext Engineering & Agent Infrastructure. Build the platform-level systems for context management, session state, and memory that all of Harvey’s agents and products rely on.Model Integration & Routing. Own the infrastructure that lets Harvey onboard new foundation models fast and route to the right one for every task - a capability every product team depends on.Evaluation Infrastructure. Build the shared eval tooling and frameworks that let every team across Harvey measure and improve AI quality systematically.Shared Abstractions. Create the SDKs, platform primitives, and developer tooling that make it dramatically easier for product teams to ship AI-powered features.What You’ll DoDesign and build abstractions and platform-level systems that improve all of Harvey’s agentic products.Own infrastructure for model integration, routing, and evaluation that helps Harvey choose and deploy the right foundation model for any given context.Build evaluation frameworks and tooling that let every team across Harvey iterate on AI quality effectively.Partner closely with product engineering teams, PMs, and design to launch cutting-edge AI products.Evaluate, prototype, and integrate the latest advancements in AI and agentic systems as they emerge.What You Have5+ years of experience building backend systems, with at least 1+ year focused on AI/ML engineering. Staff candidates will typically have 8+ years and a track record of technical leadership across teams.Experience building and shipping multi-model or multi-provider AI systems in production.Familiarity with context management, session state, or memory systems in AI or distributed systems. You’ve thought about what the model sees and why it matters.A track record of building internal platforms, SDKs, or shared infrastructure that other engineering teams actually adopted - and an understanding of why developer experience matters as much as raw capability.Strong judgment about abstractions. Opinionated about good design but pragmatic about shipping incrementally.Excitement about agentic AI and the infrastructure challenges of making autonomous systems reliable when the stakes are real.A bias toward full ownership: you navigate ambiguity well and don’t wait for a roadmap to start solving problems.Bonus: experience building evaluation frameworks, working with agent/function-calling architectures, familiarity with legal or other high-stakes professional services domains, or time at early-stage or hyper-growth startups where the underlying technology changes regularly.Compensation$220,000 - $300,000Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai

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About the RoleYou are the engineering backbone of the internal tools team. Building and maintaining the platforms that every team in the company relies on. Your work directly increases organizational efficiency and enables teams to move faster.You’ll own systems end-to-end, from scoping and architecture through production deployment and iteration, connecting multiple business systems into a seamless, reliable internal ecosystem.What You'll DoBuild & ShipDesign, build, and maintain internal platforms and tools that serve People, Finance, Ops, Sales, and Engineering teams.Own features end-to-end: requirements, architecture, implementation, testing, deployment, and monitoring.Write clean, well-tested, production-grade code. You hold yourself to the same bar as customer-facing products.Architecture & IntegrationBuild API-first integrations across the internal ecosystem — connecting HRIS, CRM, finance platforms, knowledge management, and developer tools into a coherent stack.Design for reliability, performance, and scale — what you build today must hold as the company grows 5–10x.Eliminate data silos. Build clean data pipelines that maintain a single source of truth across systems.Own your services in production: monitoring, alerting, incident response, and post-mortems.AI & AutomationBuild AI/LLM-powered features into internal workflows — automating approvals, knowledge retrieval, reporting, content generation, and operational processes.Move fast from prototype to production. You know the difference between a demo and a system that works at scale.Stay current on emerging AI capabilities and proactively identify where they unlock step-change improvements in internal productivity.Collaboration & InfluenceWork directly with business stakeholders to understand pain points and translate them into technical solutions. You don’t wait for a spec — you help shape it.Pair with and mentor junior engineers. Raise the technical bar through code reviews, design reviews, and leading by example.Influence technical direction: propose architectural improvements, challenge assumptions, and drive best practices across the team.What You Will NeedMust-Have5+ years of professional software engineering experience, with meaningful time spent building internal tools, platforms, or business systems.Strong full-stack or backend engineering skills. Proficient in at least one of: Python, Go, TypeScript/Node.js, or Java.Solid understanding of cloud infrastructure (GCP/AWS/Azure), containerisation (Docker/Kubernetes), CI/CD pipelines, and modern DevOps practices.Hands-on experience building and maintaining API integrations between third-party SaaS platforms (e.g., Workday, Salesforce, Slack, NetSuite).Strong data fundamentals: relational databases, data modelling, ETL/ELT pipelines, and working knowledge of SQL.Comfort with ambiguity. You can take a vague business problem, break it down, and deliver a working solution without heavy hand-holding.Clear communicator who can explain technical tradeoffs to non-technical stakeholders.Nice-to-HaveExperience with workflow orchestration tools (Temporal, Airflow, Prefect) or integration platforms (Workato, Tray.io, MuleSoft).Frontend experience with React, Next.js, or equivalent modern frameworks.Familiarity with HRIS, ERP, or people systems data models and processes.Experience at a high-growth or AI-native company.Contributions to developer experience tooling, CLIs, or internal SDKs.Experience building or integrating AI/LLM-powered features — not just experimenting, but shipping to real users.How We WorkWe operate as a small, senior, hands-on team. Engineers own features end-to-end — from design discussion through production monitoring.Code reviews and design reviews are expected for all meaningful changes. We discuss architecture openly, make decisions quickly, and ship frequently.Interview processIf there appears to be a fit, we'll reach out to schedule 3, but no more than 4 interviews.Applications are evaluated by our technical team members. Interviews will be conducted via virtual meetings and/or onsite.We value transparency and efficiency, so expect a prompt decision. If you've demonstrated the exceptional skills and mindset we're looking for, the process to offer may be shorter.

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About UsHarmattan AI is a next-generation defense prime building autonomous and scalable defense systems. Following the close of a $200M Series B, valuing the company at $1.4 billion, we are expanding our teams and capabilities to deliver mission-critical systems to allied forces.Our work is guided by clear values: building technologies with real-world impact, pursuing excellence in everything we do, setting ambitious goals, and taking on the hardest technical challenges. We operate in a demanding environment where rigor, ownership, and execution are expected.About the RoleAs a System Architect, you will own the end-to-end architecture, system definition, and strategic implementation for our entire portfolio of robotic and autonomous defense systems—from long-term vision to field deployment. You will collaborate closely with executive leadership and technical leads, forming a critical partnership with the Product Manager to ensure efficiency and alignment across the organization.This pivotal role drives strategic programs including anti-drone warfare, ISR and strike systems, equipment fusion (especially aeronautics), and C2 and AI.Key ResponsibilitiesSystem-of-Systems Design & Strategy: Translate complex strategic goals into global, system-of-systems designs. Define and champion the overall system architecture strategy across the enterprise, ensuring coherence from concept through deployment.Architectural Sizing & Verification: Ensure all systems meet defined needs and are correctly sized through rigorous verification of scope, complex system-of-systems simulations, and precise system sizing. Guide major technical investment decisions.Technical Leadership & Coordination: Coordinate large, multidisciplinary engineering organizations and provide overarching technical leadership across cross-functional design efforts (mechanical, electrical, software, GNC, ML, product). Ensure long-term performance, robustness, and strategic reliability across the enterprise.Specification & Integration Governance: Govern system integration standards and validation processes. Manage the complex process of specification management by ensuring all architectural prerequisites are met. Drive multi-system architecture reviews for enterprise design consistency.Continuous Improvement: Implement and institutionalize processes to enhance requirements traceability, system documentation standards, and validation workflows across the entire engineering organization.Candidate RequirementsExperience & Education10+ years of experience in systems engineering or architecture, with significant time in a senior or lead role.MSc in Engineering (any field); PhD is a plus.Experience in the defense sector is mandatory; experience with drones or autonomous platforms is a significant plus.Domain ExpertiseStrong knowledge in one or more of the following specializations:C2 (Command and Control) & AIISR (Intelligence, Surveillance, and Reconnaissance)Strike UAV and loitering munitionsAnti-drone warfare / Counter-UASUAV equipment and sensor fusionSkills & CompetenciesExpert in defining and leading the full lifecycle of complex, multi-system and system-of-systems architectures.Strategic, analytical, and mission-driven with expertise in strategic requirements engineering and high-level trade-off analysis.Deep engineering understanding across mechanical, electrical, embedded, and enterprise software systems.Proven ability to coordinate large, multi-disciplinary engineering organizations and manage complex technical and strategic interfaces.Exceptional communication, presentation, and technical documentation skills for both technical and executive audiences.Location and CommitmentsContract Type: Full-time / PermanentWork Schedule: Arlington, Virginia / On-siteCompensation: $200K-$220K + equity + benefitsWe look forward to hearing how you can help shape the future of autonomous defense systems at Harmattan AI.

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About the TeamThe Integrity team at OpenAI is dedicated to ensuring that our cutting-edge technology is not only revolutionary, but also secure from a myriad of adversarial threats. We strive to maintain the integrity of our platforms as they scale. The Integrity team is at the front lines of defending against financial abuse, scaled attacks, and other forms of misuse that could undermine the user experience or harm our operational stability.About the RoleAs a Machine Learning Engineer in OpenAI's Applied Group, you will have the opportunity to work with some of the brightest minds in AI. You'll contribute to deploying state-of-the-art models in production environments, helping turn research breakthroughs into tangible solutions that improve the trust and safety of our platform. If you're excited about fine tuning LLMs and building ML models this role is your chance to make a significant mark.In this role, you will:Innovate and Deploy: Design and deploy advanced machine learning models that solve real-world problems. Bring OpenAI's research from concept to implementation, creating AI-driven applications with a direct impact.Collaborate with the Best: Work closely with researchers, software engineers, and product managers to understand complex business challenges and deliver AI-powered solutions. Be part of a dynamic team where ideas flow freely and creativity thrives.Optimize and Scale: Implement scalable data pipelines, optimize models for performance and accuracy, and ensure they are production-ready. Contribute to projects that require cutting-edge technology and innovative approaches.Learn and Lead: Stay ahead of the curve by engaging with the latest developments in machine learning and AI. Take part in code reviews, share knowledge, and lead by example to maintain high-quality engineering practices.Make a Difference: Monitor and maintain deployed models to ensure they continue delivering value. Your work will directly influence how AI benefits individuals, businesses, and society at large.You might thrive in this role if you:Master's/  PhD degree in Computer Science, Machine Learning, Data Science, or a related field. Demonstrated experience in deep learning and transformers modelsProficiency in frameworks like PyTorch or TensorflowStrong foundation in data structures, algorithms, and software engineering principles.Experience with search relevance, ads ranking  or LLMs is a plus.Are familiar with methods of training and fine-tuning large language models, such as distillation, supervised fine-tuning, and policy optimizationExcellent problem-solving and analytical skills, with a proactive approach to challenges.Ability to work collaboratively with cross-functional teams.Ability to move fast in an environment where things are sometimes loosely defined and may have competing priorities or deadlinesEnjoy owning the problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job doneAbout 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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WHO WE AREEma is building the next generation AI technology to empower every employee in the enterprise to be their most creative and productive. Our proprietary tech allows enterprises to delegate most repetitive tasks to Ema, the AI Employee.We are founded by ex-Google, Coinbase, and Okta executives and serial entrepreneurs. We've raised capital from notable investors including Accel Partners, Naspers, and Section32, along with prominent Silicon Valley angels such as Sheryl Sandberg (Facebook/Google), Jerry Yang (Yahoo), Dustin Moskovitz (Facebook/Asana), David Baszucki (Roblox CEO), and Gokul Rajaram (DoorDash, Square, Google).Our team comprises engineers from Google, Microsoft Research, Facebook, Square/Block, and Coinbase — with most hailing from top-tier institutions like Stanford, MIT, UC Berkeley, CMU, and IIT.THE ROLEAs an Engineering Leader at Ema, you will build and lead a high-performance engineering organization — setting the technical standard for reliability and demonstrating a strong execution mindset. You will collaborate directly with the Head of Engineering and co-founders to architect and drive the product roadmap from an engineering standpoint.We are looking for a leader who combines deep, hands-on technical expertise with the executive presence required to attract, mentor, develop, and retain top-tier engineering talent.WHAT YOU'LL DOTeam Building & Engineering CultureRecruit, hire, and develop senior engineers across multiple sub-teams: cloud infrastructure, data platform, ML operations, and developer experience.Establish engineering standards, code review culture, on-call expectations, and a bias-toward-shipping mentality balanced with production rigor.Coach and grow senior/staff engineers into technical leaders; manage engineering managers as the organization scales.Technical Strategy & ExecutionSet the 6–18 month platform roadmap in partnership with engineering teams, balancing foundational investments against product-driven urgency.Make high-stakes architectural decisions — build vs. buy, migration strategies, technology bets — and own the outcomes.Drive cross-functional alignment with product, ML/AI research, and go-to-market teams to ensure the platform evolves in lockstep with customer and product needs.Operational ExcellenceOwn production health for all platform services: incident response, postmortems, SLO tracking, and capacity planning.Establish and iterate on engineering practices that keep the team shipping fast without compromising reliability.Participate in executive-level reviews on infrastructure spend, system health, and engineering velocity.WHAT YOU BRINGRequired12+ years of software engineering experience, with 4+ years leading platform or infrastructure teams of 8+ engineers at high-growth startups or top-tier tech companies.Deep, hands-on expertise in distributed systems.Production experience with container orchestration (Kubernetes), microservices architecture, and at least two major cloud providers (GCP, AWS, Azure).Strong programming ability in Go and Python; you still read code daily and can mentor engineers on systems-level design.Experience building quality software using AI-driven tools.Track record of building internal platforms from scratch that other engineering teams adopt and depend on.Expertise in database internals and performance tuning across SQL, NoSQL, and graph or vector data stores; working knowledge of CAP theorem trade-offs in production.Proven ability to hire, develop, and retain high-caliber engineers in competitive markets.Strongly PreferredExperience building infrastructure for AI/ML workloads: model serving, GPU scheduling, training pipelines, or inference optimization.Familiarity with vector databases, embedding pipelines, RAG architectures, or LLM orchestration frameworks.Experience operating multi-tenant SaaS platforms with strict data isolation and compliance requirements (SOC 2, GDPR, HIPAA).Background in real-time data streaming (Kafka, Pulsar, Flink) and event-driven architecture.Prior success driving large-scale cloud cost optimization initiatives (saving $1M+ annually).WHY EmaGreenfield technical challenges at the intersection of AI infrastructure and enterprise scale — you will build systems that don't exist yet.Direct access to founders and the CTO; your decisions shape the company's technical trajectory.A team of exceptional engineers from Google, Meta, Microsoft Research, and top CS programs worldwide.Competitive compensation, meaningful equity, and the upside of an early-stage company backed by world-class investors.Ema is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

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About FurtherAIInsurance is a $7 trillion industry that still runs on PDFs, emails, and manual review. At FurtherAI, we're building the AI workspace that changes that — automating the complex, document-heavy workflows that underwriters, claims teams, and brokers deal with every day so insurance professionals can focus on the work that actually matters.We've raised $30M total, including a $25M Series A led by a16z (one of the largest Series A rounds in insurance AI history), with participation from Y Combinator, Nexus Venture Partners, and others. We've grown 10x in revenue this year, and our customers include some of the largest carriers, MGAs, and brokers in the world — including a top-5 global insurance company. Our forward-deployed engineering model means we work side-by-side with customers to stand up real workflows that deliver measurable results fast.About the RoleInsurance Engineer is a new kind of role. It sits at the intersection of insurance domain expertise, technical implementation, and product thinking — and it doesn't really exist anywhere else yet.You're an insurance expert who builds. You can look at a messy workflow, break it into components an AI system can execute, define what "correct" looks like, and measure whether the system actually gets there. You know the Sub/Quote/Bind flow not because someone explained it to you — but because you've lived it. And now you're ready to apply that expertise to build the systems that automate it.You'll own the full lifecycle of AI extraction workflows on our platform: scoping, architecture, prototyping, evaluation, and iteration. You'll work alongside our Forward Deployed Engineers and customers to ship workflows that perform in production at some of the largest carriers, MGAs, and brokers in the world.If you've spent years in insurance operations and you're ready to build the systems that automate it — this is the job.What You'll OwnWorkflow design and build. You'll take complex insurance processes — submission intake, policy comparison, underwriting audits, claims workflows — and turn them into structured, testable AI workflows from scratch.Ground truths and evals. You'll define what accurate, complete outputs look like for every workflow. You'll build evaluation sets, run continuous benchmarks, and surface quality gaps before customers do.Customer implementations. You'll work directly with customers alongside FDEs to configure, test, and iterate workflows toward production — bringing insurance process expertise and technical judgment to every deployment.The bridge between domains. You're the person in the room who understands both sides — able to translate between what an underwriter needs and what an engineering team builds.Who You AreAn insurance operator who thinks like a builder.You've spent meaningful time inside the insurance market — at a carrier, MGA, TPA, broker, or insurtech. You know the Sub/Quote/Bind flow. You understand where the friction lives and why it matters. That domain expertise is your edge — and you're ready to use it to build.Comfortable working technically alongside engineers.You don't need to be a software engineer, but you can write Python, SQL, or equivalent to test logic and validate workflow outputs. You move fast without waiting for someone else to prototype an idea.A structured thinker.You can take a messy insurance process and break it into clean, testable components. You know how to define what "correct" looks like — and build evaluations that surface real quality issues, not just happy path tests.Implementation-minded and customer-facing.You've worked directly with customers in a technical capacity — solutions engineering, professional services, or implementation — and you know how to navigate the gap between what a customer asks for and what actually needs to be built.Qualifications4–8 years in insurance operations, technical implementation, solutions engineering, or technical product management — ideally with direct insurance industry exposure at a carrier, MGA, TPA, broker, or insurtechHands-on familiarity with core insurance workflows: Sub/Quote/Bind, underwriting, policy management, or claimsTech-forward mindset — you're already using ChatGPT, Claude, and other AI tools in your personal and professional life, not waiting to be told toImplementation-minded — you've worked directly with customers or end users in a technical capacity and know how to navigate the gap between what a customer asks for and what actually needs to be builtAbility to prototype or script workflows — Python, SQL, JSON/YAML configs, or similar; you move fast technically without waiting for an engineerComfort with evaluation concepts: defining ground truth, measuring precision/recall tradeoffs, and building eval sets that surface real quality issuesWhy FurtherAIReal ownership. You'll be an early team member shaping a category-defining product in a $7 trillion industry.Hands-on impact. Every workflow you build ships to real customers at some of the largest insurance companies in the world.Strong backing. $30M raised, a16z-led, 10x revenue growth — the resources and momentum to build something lasting.Collaborative, low-ego team. Close-knit team working across product, engineering, and go-to-market. No silos.Competitive compensation. Base salary, equity, and full benefits.

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About Distyl AI Distyl is an applied AI technology company partnering with the world’s most ambitious institutions to rearchitect critical operations for the frontier of AI. Our customers include the largest companies in telecom, healthcare, insurance, manufacturing, consumer goods, and global social organizations. We research and deploy technologies that power AI-native operations — both for our partners and for Distyl itself. Our work spans research into self-constructing systems, the development of the most reliable execution of AI systems, and products that transform mission-critical workflows. As a result, Distyl's technologies affect some of the world's largest operations — from hundreds of millions of consumer interactions to tens of millions of supply chain transactions and millions of patient journeys. Distyl is backed by leading investors including Lightspeed Venture Partners, Khosla Ventures, Coatue, DST Global, and the board-members of 20+ F500s. The results reflect this approach: a 100% production deployment success rate for our customers and one of the few enterprise AI companies to run a profitable business.What We’re Looking ForWe’re opening an office in London, UK and looking for AI Engineers to design and deploy production-grade AI systems powered by LLMs.At Distyl, AI Engineers work directly with Fortune 500 companies to transform complex workflows using cutting-edge AI. You’ll build and ship real-world AI applications — from intelligent agents to full-stack AI products — and see them operate at scale in mission-critical environments.This role is highly hands-on. You’ll collaborate closely with customers, define system architectures, and build reliable, high-impact AI systems from prototype to production. Engineers at Distyl also help shape technical direction across major customer engagements, guiding enterprise teams through AI adoption and deployment.Key ResponsibilitiesBuild Production AI Systems: Design, develop, and deploy robust AI applications using LLMs, including prompt engineering, agent workflows, tool use, and full-stack AI productsWork Directly with Customers: Partner closely with enterprise stakeholders to understand complex problems and translate them into impactful AI solutionsLead System Architecture: Design scalable architectures for production AI systems, balancing performance, reliability, cost, and maintainabilityDevelop Our Internal Platform: Contribute to Distillery, our internal LLM application platform, by building reusable infrastructure, tools, and workflows used across customer deploymentsEvaluate AI Systems Rigorously: Develop evaluation frameworks that measure model performance across accuracy, latency, cost, reliability, and safetyShip Production-Grade Systems: Ensure systems meet high standards for observability, reliability, security, and maintainabilityRaise the Engineering Bar: Improve development workflows, evaluation practices, and deployment strategies as our AI platform continues to evolveWho You Are3+ years of professional software engineering experienceStrong proficiency in Python or TypeScriptExperience building and deploying LLM-powered applications or AI agents in productionExperience with modern LLM tooling such as LangChain, LlamaIndex, Guardrails, MCP, or agent frameworksExperience implementing RAG pipelines, tool use, or multi-step AI workflowsStrong understanding of AI system evaluation, debugging, and observabilityExperience building reliable production systems with modern DevOps practicesExperience deploying AI systems in enterprise environments is a plusExperience working across cloud platforms (AWS, GCP, or Azure) is a plusExperience with agent architectures and long-horizon task execution is a plusFamiliarity with responsible AI practices, including auditability and governance is a plusWhat We OfferCompetitive salary, meaningful equity, and a comprehensive benefits packagePrivate medical, dental, and vision cover for you and your familyGenerous holiday allowanceLunch provided on office daysAccess to state-of-the-art models, generous usage of modern AI tools, and real-world business problemsOwnership of high-impact projects across top enterprisesA mission-driven, fast-moving culture that prizes curiosity, pragmatism, and excellence

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About UsHarmattan AI is a next-generation defense prime building autonomous and scalable defense systems. Following the close of a $200M Series B, valuing the company at $1.4 billion, we are expanding our teams and capabilities to deliver mission-critical systems to allied forces.Our work is guided by clear values: building technologies with real-world impact, pursuing excellence in everything we do, setting ambitious goals, and taking on the hardest technical challenges. We operate in a demanding environment where rigor, ownership, and execution are expected.RoleAs an Aerodynamics Methodology & Software Engineer at Harmattan, you will bridge the gap between aerospace physics and high-performance software engineering. Your mission is to professionalize our internal computational ecosystem, manage our HPC/Cloud infrastructure, and transform research-grade scripts into production-ready engineering software. You will act as the lead architect for our agentic AI workflows, developing custom MCP servers and LLM-ready repositories to automate complex simulation loops and design optimisations. You are the engineer of the automated toolchains that allow our team to iterate on UAV designs with unprecedented speed and fidelity.ResponsibilitiesSoftware Professionalization: Refactor research scripts and "specialist tools" into modular, high-performance, and maintainable Python/C++ libraries. Implement robust unit-testing and documentation standards. Make sure the team members follow the structure when developing code.AI-Augmented Engineering & Orchestration: Architect agentic workflows and custom MCP (Model Context Protocol) servers to bridge LLMs with internal CFD solvers and databases; codify engineering tribal knowledge into SKILLS.md or CLAUDE.md files to enable AI-driven code refactoring, automated simulation setup, and intelligent data analysis.MDAO Toolchain Integration: Architect a unified design environment by developing APIs and automated workflows that link disparate tools (e.g., OpenVSP, XFoil, and OpenFOAM) into seamless optimization loops.Infrastructure & Scalability: Manage and optimize our calculation infrastructure, including Linux-based HPC clusters (Slurm) and/or Cloud computing (AWS/Azure).Aero Database (ADB) Management: Design the data architecture for storing and retrieving high-dimensional aerodynamic results, ensuring the GNC and flight physics teams have "single-source-of-truth" access to vehicle performance data.RequirementsEducation: B.S., M.S., or Ph.D. in Aerospace Engineering, Computer Science, or Informatics with a proven track record in the aerospace sector.Aerospace Background: Familiarity with the aerospace physics, data structures and I/O of industry tools such as OpenFOAM, ANSYS, XFOIL, OpenVSP, or QProp.Advanced Programming: Expert proficiency in Python (NumPy, SciPy, Pandas) and ideally C++.Modern AI & Agentic Systems: Proven ability to develop LLM-integrated tools and MCP servers that automate engineering tasks; experience maintaining "AI-ready" repositories using structured instruction files and building neural surrogate models to accelerate physical simulations.DevOps & Infrastructure: Knowledge of Git/GitLab (CI/CD, Runners) and Linux/Unix environments. Experience with Bash scripting and Cloud-scale computing (AWS).Nice-to-HaveNumerical Methods: Hands-on experience using CFD or other physical solvers. Able to select appropriate physics models (for example turbulence models), configuring numerical schemes, and fine-tuning solvers.Machine Learning in Data Science: Knowledge in setting up surrogate models and tools for engineering practices (surrogate models)We look forward to hearing how you can help shape the future of autonomous defense systems at Harmattan AI.

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The RoleWe're looking for a talented, hungry, and technically excellent Product Engineer to join our team.In this role you will dream up, build, and ship LM Studio features to millions of users worldwide, at a fast clip. You will be intermixing UI work with systems engineering, design, and applied AI / agentic engineering work.You may be a good fit if you love building software products, have an innate talent for crafting product experiences, and you approach technical problems with a scientific method mindset. Holistic understanding of software systems and the ability to work across the stack is a must. Experience building desktop applications is a big plus, but not required.This role is in-person in our New York City office. Relocation assistance is possible. In your application, please share technical details about your expertise and things that you've built.Relevant experience: React, TypeScript, Electron, Swift, Objective-C, C++.LM StudioWe aim to build delightful and potent creation tools for AI. We are a small team based in New York. Everyone on the team is IC-minded, intellectually curious, self-motivated, and loves software. We care deeply about our user community and we strive to build canonical software that users and developers love.Our Interview ProcessWe are looking for engineering excellence and strong values / cultural fit. If your application appears to be a good match we'll reach out to schedule an initial call. If all goes well, we will proceed to 2-3 technical interviews. The final step in the process is an onsite interview in our New York office, where you will work through several more technical sessions focused around system design and architecture, meet the team and see how we work.

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About the TeamThe Safety Systems team is dedicated to ensuring the safety, robustness, and reliability of AI models and their deployment in the real world.Building on the many years of our practical alignment work and applied safety efforts, Safety Systems addresses emerging safety issues and develops new fundamental solutions to enable the safe deployment of our most advanced models and future AGI, to make AI that is beneficial and trustworthy.Learn more about OpenAI’s approach to safetyAbout the RoleAs a Data Scientist in Safety Systems, you will establish the data-driven approach for understanding, evaluating, and monitoring the safety of our production systems. You should expect to collaborate with our partners across the company to define north-star metrics, own and implement the statistical methods to productionize those metrics, conduct analysis to understand the impact of our products, and establish source-of-truth dashboards that the entire company can use to answer safety-related questions. Most importantly, you will be a core member of the Safety Systems team, collaborating with researchers and engineers to advance our goals of safe, robust, and reliable AI.This role is based in our San Francisco HQ. We offer relocation assistance to new employees.In this role, you will:Lead our efforts in understanding and measuring the real-world safety impacts of OpenAI’s current and upcoming productsUncovering new ways to improve our approaches to measuring and mitigating harm and abuseDevelop and implement statistical methods necessary to operationalize safety-related metricsProvide direction, guidance, and coordination of projects in the spaceEstablish a data-driven culture within Safety Systems by driving the definition, tracking, and operationalizing of feature-, product-, and company-level metricsCreate and disseminate dashboards, reports, and tools that enable the team and company to answer safety-related questions independentlyDevelop safety data flywheel and provide safety research with production insights/data for training and evaluation.You might thrive in this role if you have:5+ years experience in a quantitative role navigating highly ambiguous environments, ideally as a founding data scientist or team lead at a hyper-growth product company or research orgProven leadership skills, including leading multiple data scientists and cross-functional teamsExpertise in defining and implementing metrics, with a track record of operationalizing new feature and product-level metrics from scratchExcellent communication skills with demonstrated ability to communicate with product managers, engineers, and executives alikeStrategic insights that extend beyond traditional statistical significance testing.You could be an especially great fit if you have:Experience in trust and safety, integrity, anti-abuse, or related fieldsDemonstrated prior experience in NLP, large language models, or generative AIStrong statistical background, including knowledge of sampling, regression, causal analysis, and moreAbout 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 UsAt LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale.Today, LangChain, LangGraph, LangSmith, and Agent Builder are used by teams shipping real AI products across startups and large enterprises. Millions of developers trust LangChain to power AI teams at companies like Replit, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, and 35% of the Fortune 500.With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world.About the TeamThe Deployed Engineering team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on.This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite.Deployed Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform.About the RoleThe Deployed Engineer…You’ll work on some of the hardest problems in applied AI — not demos, not research, but systems that real teams depend on in production. The feedback loop is fast, the impact is visible, and the work you do directly shapes how AI agents are built in the real world.Location(s)West: San Francisco, Pacific Northwest, Southern CaliforniaCentral: Austin, Chicago, DenverEast: New York, AtlantaEMEA: London, AmsterdamToronto, CanadaWhat You’ll DoCo-architect and co-build production AI agents with customer engineering teamsOwn the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluationsHelp customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflowsAdvise customers post-sale on architecture, best practices, and roadmap-level decisionsRun technical demos, trainings, and workshops for developer audiencesSurface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customersOccasionally contribute code upstream when it meaningfully improves customer outcomesWhat You’ll Bring3+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, founding/product engineering), ideally in a startup or scale-upStrong Python, JavaScript and systems fundamentalsHave designed agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handlingAre comfortable working directly with customers during POCs, architecture reviews, and technical evaluationsCan explain technical tradeoffs clearly and build trust with developer audiencesTake responsibility for outcomes, not just recommendationsHave a bias toward action and enjoy figuring things out as you goAre excited about operating AI agents in production, not just building demosNice to Have’s:You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworksWorked with LLM evaluation, observability, or guardrailsHave experience with cloud environments (AWS, GCP, Azure), containers, and basic Kubernetes conceptsHave shipped and operated production software and are comfortable owning systems under real-world constraintsCompensation & BenefitsWe offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Benefits include things like medical, dental, and vision coverage, flexible vacation, a 401(k) plan, and life insurance. Actual compensation and offerings will vary based on role, level, and location. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations.

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Company OverviewDeepgram is the leading platform underpinning the emerging trillion-dollar Voice AI economy, providing real-time APIs for speech-to-text (STT), text-to-speech (TTS), and building production-grade voice agents at scale. More than 200,000 developers and 1,300+ organizations build voice offerings that are ‘Powered by Deepgram’, including Twilio, Cloudflare, Sierra, Decagon, Vapi, Daily, Cresta, Granola, and Jack in the Box. Deepgram’s voice-native foundation models are accessed through cloud APIs or as self-hosted and on-premises software, with unmatched accuracy, low latency, and cost efficiency. Backed by a recent Series C led by leading global investors and strategic partners, Deepgram has processed over 50,000 years of audio and transcribed more than 1 trillion words. There is no organization in the world that understands voice better than Deepgram.Company Operating RhythmAt Deepgram, we expect an AI-first mindset—AI use and comfort aren’t optional, they’re core to how we operate, innovate, and measure performance.Every team member who works at Deepgram is expected to actively use and experiment with advanced AI tools, and even build your own into your everyday work. We measure how effectively AI is applied to deliver results, and consistent, creative use of the latest AI capabilities is key to success here. Candidates should be comfortable adopting new models and modes quickly, integrating AI into their workflows, and continuously pushing the boundaries of what these technologies can do.Additionally, we move at the pace of AI. Change is rapid, and you can expect your day-to-day work to evolve just as quickly. This may not be the right role if you’re not excited to experiment, adapt, think on your feet, and learn constantly, or if you’re seeking something highly prescriptive with a traditional 9-to-5.OpportunityDeepgram is seeking a Senior Applied Engineer to join our Applied Engineering team, operating in the Forward-Deployed Engineer (FDE) role with a focus on federal customers. In this role, you will embed directly with our most strategic federal accounts to lead complex deployments of Deepgram's Voice AI platform in production environments where mission performance matters, delivery is urgent, and ambiguity is the default. You will own the full technical lifecycle of federal engagements, from initial discovery and proof-of-concept through production deployment and ongoing optimization. You'll map customer problems, structure delivery, and ship solutions fast. This includes scoping, sequencing, and building full-stack integrations that create measurable mission impact while driving clarity across internal and external teams. Along the way, you'll identify reusable patterns, codify best practices, and share field signals that influence Deepgram's product roadmap. As a member of the Applied Engineering team, you'll serve as the trusted technical thought partner for federal stakeholders, guiding adoption, maximizing operational value, and ensuring successful deployments at scale. While your engagements will primarily involve federal customers, you'll remain a core part of the broader Applied Engineering team and may contribute to commercial engagements where your expertise is valuable.Note: this role is based remotely out of the Washington D.C. Metropolitan area.About Applied Engineering at DeepgramThe Applied Engineering (AppEng) team at Deepgram combines the functions that other companies might separate into Sales Engineering, Solutions Architecture, Implementation, Forward-Deployed Engineering, and Technical Support. We serve as the technical interface between Deepgram and our customers throughout their entire journey, from initial discovery and proof-of-concept, through implementation and onboarding, to ongoing technical support. We work closely with our Customer Success and Developer Relations (DevRel) teams to ensure a positive, growth-focused experience for our customers, as well as with Product and Engineering teams to deliver solutions that meet customer needs. This unified approach allows us to provide comprehensive technical guidance and build deeper relationships with our customers.As a Senior Applied Engineer operating in the FDE role for federal engagements, you'll work with a high degree of autonomy in customer environments that often have unique infrastructure constraints, compliance requirements, and security considerations. Your work will directly shape how federal agencies leverage Voice AI to achieve their missions.What You'll DoOwn technical delivery across federal deployments, from first prototype to stable productionEmbed deeply with federal customers to design and build mission-critical applications powered by Deepgram's Voice AI modelsLead technical discovery and solution design for federal prospects and customers, partnering with Account Executives to navigate complex government sales and procurement cyclesPrototype and build full-stack integrations using Python, JavaScript, Rust, or comparable stacks that deliver real mission impactEnable successful deployments across customer environments by delivering observable systems spanning infrastructure through applicationsProactively guide federal stakeholders on maximizing operational value from Deepgram's platform, including performance optimization and deployment strategiesScope work, sequence delivery, and remove blockers early, making deliberate trade-offs between scope, speed, and qualityBuild and manage relationships with customer leadership and technical stakeholders to ensure successful deployment and scaleContribute directly to code when clarity or momentum depends on itCodify working patterns into tools, playbooks, reference architectures, and building blocks the broader team can useShare field feedback with Product and Engineering to influence model and product developmentServe as an escalation point for complex technical issues in federal deploymentsAnalyze deployment patterns to identify product improvement opportunities and inform Deepgram's federal go-to-market strategyTime Allocation40% — Embedded customer delivery: deployments, integrations, and technical problem-solving at federal customer sites and facilities25% — Pre-sales technical engagement: discovery, demos, proof-of-concepts, and proposal support20% — Building reusable solutions, automation, documentation, and reference architectures15% — Internal collaboration: product feedback, knowledge sharing, and contributing to Applied Engineering strategyYour First 90 DaysFirst 30 Days: Complete comprehensive onboarding to understand Deepgram's technology, products, and competitive landscape. Gain proficiency with our core APIs and documentation. Shadow active customer engagements across both commercial and federal accounts to build familiarity with how the Applied Engineering team operates, the deployment patterns we use, and the specific requirements of government environments.60 Days: Begin taking ownership of federal customer engagements, leading technical discovery and developing proof-of-concepts for government prospects. Start contributing to federal-specific technical content, reference architectures, and deployment guides. Participate in sales strategy sessions and provide technical insights on active federal deals.90 Days: Own the full technical relationship with assigned federal accounts. Develop and deliver complex solutions addressing specific mission challenges. Establish patterns for repeatable federal deployments and begin contributing to the team's federal go-to-market methodology.You'll Love This Role If YouThrive in high-ambiguity, mission-driven environments where you need to move fast and make sound decisions under pressureAre passionate about translating complex technical capabilities into real operational value for government missionsEnjoy embedding deeply with customers, building trust, and becoming their go-to technical partnerFind satisfaction in shipping production systems that make a tangible differenceAre energized by the challenge of deploying cutting-edge Voice AI in complex, constrained environmentsSee yourself as an engineer first who happens to be great with customers, not the other way aroundCan ruthlessly prioritize across multiple projects and operate with high autonomyIt's Important To Us That You HaveActive Top Secret/SCI (TS/SCI) security clearance, or equivalent5+ years of engineering or technical deployment experience, ideally in customer-facing or government environmentsStrong software engineering background with professional development experience in at least one modern programming language, such as Python, JavaScript, or similarProven ability to scope and deliver complex systems in fast-moving or ambiguous contextsExperience building and deploying production systems in government or similarly constrained environmentsExcellent verbal and written communication skills with the ability to translate technical concepts for both technical and non-technical stakeholders, including senior government leadershipTrack record of navigating complex sales or procurement cycles in the federal spaceWillingness to travel up to 50%, including on-site work at government facilitiesIt Would Be Great if You HadExperience with speech recognition, NLP, AI/Voice agents, or related AI technologiesFamiliarity with cloud deployment models (AWS GovCloud, Azure Government, etc.), Kubernetes, Terraform, and related infrastructureExperience building or deploying systems powered by LLMs or generative models, with an understanding of how model behavior affects product experienceKnowledge of FedRAMP, FISMA, or other government compliance frameworksExperience with API-first products and developer toolsBackground in sales methodologies such as MEDDIC or Solution Selling, particularly in government contextsExperience developing automation solutions, self-service tools, and technical documentation for customer enablementBenefits & Perks*Holistic healthMedical, dental, vision benefitsAnnual wellness stipendMental health supportLife, STD, LTD Income Insurance PlansWork/life blendUnlimited PTOGenerous paid parental leaveFlexible schedule12 Paid US company holidaysQuarterly personal productivity stipendOne-time stipend for home office upgrades401(k) plan with company matchTax Savings ProgramsContinuous learningLearning / Education stipendParticipation in talks and conferencesEmployee Resource GroupsAI enablement workshops / sessions*For candidates outside of the US, we use an Employer of Record model in many countries, which means benefits are administered locally and governed by country-specific regulations. Because of this, benefits will differ by region — in some cases international employees receive benefits US employees do not, and vice versa. As we scale, we will continue to evaluate where we can create more alignment, but a 1:1 global benefits structure is not always legally or operationally possible.Backed by prominent investors including Y Combinator, Madrona, Tiger Global, Wing VC and NVIDIA, Deepgram has raised over $215M in total funding. If you're looking to work on cutting-edge technology and make a significant impact in the AI industry, we'd love to hear from you!Deepgram is an equal opportunity employer. We want all voices and perspectives represented in our workforce. We are a curious bunch focused on collaboration and doing the right thing. We put our customers first, grow together and move quickly. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, gender identity or expression, age, marital status, veteran status, disability status, pregnancy, parental status, genetic information, political affiliation, or any other status protected by the laws or regulations in the locations where we operate.We are happy to provide accommodations for applicants who need them.

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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:Crusoe is on a mission to accelerate the abundance of energy and intelligence. As the Senior Director of Engineering for Developer Experience, you will own and drive the strategy, execution, and culture of the team responsible for how Crusoe's engineers and non-engineers build, ship, and operate software. Crusoe is looking for a visionary to develop and further build a talented team focused on making every developer at Crusoe faster, more effective, and more empowered through world-class internal tooling, platforms, and AI-powered automation. You'll partner closely with senior engineering and product leadership to define and deliver the foundation that accelerates everything we build.What You'll Be Working On:Developer Platform & Internal Tooling: Define and execute the long-term vision for Crusoe's internal developer platform — including shared services, internal APIs, repositories, and self-service infrastructure — that enables engineering teams to move with speed and confidence.AI Platform: Rapidly develop and productionize software for the entire company. You’ll create and evangelize the golden path to productionizing AI-developed tools, supporting every team at Crusoe. You’ll tip the scales on build-vs-buy for every proposed SaaS purchase.CI/CD & DevOps Infrastructure: Oversee the design, reliability, and continuous improvement of Crusoe's CI/CD pipelines, build systems, and deployment infrastructure, ensuring engineering teams can ship safely and rapidly at scale.Engineering Productivity & Process: Define and drive org-wide engineering productivity initiatives — establishing metrics, identifying bottlenecks, and implementing tooling and process improvements that measurably improve developer experience across the company.People Leadership: Manage and grow a team of talented engineers and establish a high-performance culture rooted in accountability, innovation, and continuous learning.Cross-Functional Partnership: Collaborate with senior leaders across Engineering, Infrastructure, Security, and Product to align Developer Experience investments with company-wide engineering goals and priorities.What You'll Bring to the Team:Proven Leadership: 10+ years of software engineering experience, with at least 4+ years in senior engineering leadership roles.Developer Experience Expertise: Deep, hands-on understanding of what it takes to build great developer experience, such as internal platforms, tooling, CI/CD systems, and developer productivity programs at scale.AI Evangelist: You should be extremely fluent in agentic software development .Technical Depth: Strong engineering fundamentals with the ability to lead engineers on architecture decisions, technology choices, and complex technical trade-offs across platform and infrastructure domains.Strategic Vision with Execution Discipline: Demonstrated ability to define a roadmap for a platform or infrastructure organization and drive it to delivery through structured planning, prioritization, and cross-functional alignment.Data-Driven Approach: Experience establishing and using developer productivity metrics (e.g., DORA metrics, deployment frequency, cycle time) to identify opportunities and demonstrate impact.Communication & Influence: Exceptional communicator who can operate effectively at both the executive level and in the weeds with engineering teams — translating strategy into execution and results into business impact.Benefits:Industry competitive payRestricted Stock Units in a fast growing, well-funded technology companyHealth insurance package options that include HDHP and PPO, vision, and dental for you and your dependentsEmployer contributions to HSA accounts Paid Parental Leave Paid life insurance, short-term and long-term disability Teladoc 401(k) with a 100% match up to 4% of salaryGenerous paid time off and holiday scheduleCell phone reimbursementTuition reimbursementSubscription to the Calm appMetLife LegalCompany paid commuter benefit; $300/monthCompensation RangeCompensation will be paid in the range of up to $301,750 - $355,000 + Bonus. Restricted Stock Units are included in all offers. Compensation to be determined by the applicants 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 Mistral At Mistral we are on a mission to democratize AI, producing frontier intelligence for everyone, developed in the open, and built by engineers all over the world. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation, with teams distributed between Europe, the USA and Asia. We are creative, low-ego and team-spirited. At Mistral, we develop models for the enterprise and for consumers, focusing on delivering systems which can really change the way in which businesses operate and which can integrate into our daily lives. All while releasing frontier models open-source, for everyone to try and benefit. Mistral is hiring experts in the training of large language models and distributed systems. Join us to be part of a pioneering company shaping the future of AI. Role Summary We’re seeking highly motivated Data Quality Specialists with strong analytical skills and a keen eye for detail to join our Human Data Annotation team within the Science organisation. In this role, you will contribute to and audit human data annotations, upholding the highest standards of quality and efficiency. Key ResponsibilitiesGenerate and validate high-quality data annotations, based on guidelines and continuous feedback, for the development and evaluation of AI modelsIn collaboration with the technical team, review/audit annotations, clarify requirements, share insights, and improve annotation processes, tools, and guidelinesAbout you Relevant academic background (science, technology, engineering, mathematics)Professional proficiency in English, with strong writing and comprehension skillsOutstanding research and analytical skillsExercises great judgement with complex instructions, limited data, and/or multiple information sourcesExcellent communication, interpersonal, and organizational abilitiesAdapts easily to dynamic environments and changing requirementsAppetite for operational work and high tolerance for repetitive tasksPassionate about and committed to learning new tools and technologiesNice to have Proven track record working with dataFluency in multiple languagesExperience with code Benefits: France💰 Competitive cash salary and equity🥕 Food : Daily lunch vouchers🥎 Sport : Monthly contribution to a Gympass subscription 🚴 Transportation : Monthly contribution to a mobility pass🧑‍⚕️ Health : Full health insurance for you and your family🍼 Parental : Generous parental leave policy🌎 Visa sponsorship

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About HandshakeHandshake is the career network for the AI economy. 20 million knowledge workers, 1,600 educational institutions, 1 million employers (including 100% of the Fortune 50), and every foundational AI lab trust Handshake to power career discovery, hiring, and upskilling, from freelance AI training gigs to first internships to full-time careers and beyond. This unique value is leading to unparalleled growth; in 2025, we tripled our ARR at scale.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 feelWork hand-in-hand with world-class AI labs, Fortune 500 partners and the world’s top educational institutionsJoin a team with leadership from Scale AI, Meta, xAI, Notion, Coinbase, and Palantir, among othersBuild a massive, fast-growing business with billions in revenueAbout the RoleThe Senior Engineering Manager at Handshake AI leads a core product and platform engineering team responsible for building the systems that integrate human expertise into AI development workflows.This team owns critical infrastructure that connects talent networks, data operations, and research needs into scalable, reliable, and high-quality platforms. The role sits at the intersection of engineering, product, and operations, ensuring our systems can support rapid growth, complex workflows, and frontier AI partners. You’ll lead a team of ~9 engineers today and are expected to add leadership capacity (including managing an EM) as we scale.Location: San Francisco, CA. This is an in-office role, 5 days/week (no remote/hybrid)What You’ll DoLead, hire, and develop a high-performing engineering team building core product and platform infrastructureOwn roadmap and execution in close partnership with Product, Research, and OperationsDrive architecture and technical strategy for scalable, reliable, and extensible systemsBuild modular platforms that enable new domains, workflows, and partners to launch quicklyRaise the bar on engineering quality across reliability, observability, performance, and data integrityFoster a culture of ownership, velocity, and strong engineering fundamentals in a fast-moving, ambiguity-heavy environmentWhat We’re Looking ForEngineering leader + builder: 3+ years managing teams, plus 5+ years hands-on engineering experienceStrong people leadership: experience leading senior engineers; managing an EM (or equivalent scope) is a plusExecution in ambiguity: proven ability to align cross-functionally and deliver in fast-moving, unclear problem spacesSystems + product mindset: strong platform/distributed systems background, and the ability to turn research/ops needs into a clear roadmap, ship iteratively, and measure outcomesNice to HaveExperience with RL training infrastructure, simulation systems, or evaluation platformsHuman-in-the-loop systems (annotation, rubric tooling, QA pipelines, workflow platforms)Operations-heavy, tech-enabled environment experienceExperience building systems used by applied ML or AI research teamsPerksHandshake delivers benefits that help you feel supported—and thrive at work and in life.The below benefits are for full-time US employees.🎯 Ownership: Equity in a fast-growing company💰 Financial Wellness: 401(k) match, competitive compensation, financial coaching🍼 Family Support: Paid parental leave, fertility benefits, parental coaching💝 Wellbeing: Medical, dental, and vision, mental health support, $500 wellness stipend📚 Growth: $2,000 learning stipend, ongoing development💻 Remote & Office: Internet, commuting, and free lunch/gym in our SF office🏝 Time Off: Flexible PTO, 15 holidays + 2 flex days🤝 Connection: Team outings & referral bonusesExplore our mission, values, and comprehensive US benefits at joinhandshake.com/careers.

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Figure is an AI Robotics company developing a general purpose humanoid. Our humanoid robot is designed for commercial tasks and the home. We are based in San Jose, CA and require 5 days/week in-office collaboration. It’s time to build. Figure’s vision is to deploy autonomous humanoids at a global scale. Our Helix team is seeking an experienced Frontend Engineer to enhance our internal, web-based data and AI training tools. This role focuses on developing intuitive web interfaces that support key AI research functions, including robot data annotation, training dataset visualization, and experiment tracking. The ideal candidate has experience building rich, interactive web interfaces using React and TypeScript. Responsibilities Design and build intuitive web interfaces for robot data annotation, datasets visualization, and experiment tracking Utilize data-driven techniques to optimize interfaces for efficiency and fast iteration cycles Integrate AI models to automate manual tasks Work together with AI researchers, robot operators, and annotators to support new user experiences Requirements Strong software engineering fundamentals Bachelor's or Master's degree in Computer Science, Robotics, Engineering, or a related field Minimum of 4 years of professional, full-time experience building rich, interactive web interfaces Proficiency in React and TypeScript Bonus Qualifications Experience using data stores (Postgres, MySQL, ElasticSearch, Redis, etc.) Experience managing cloud infrastructure (AWS, Azure, GCP) Experience with Tailwind CSS Experience building data annotation and dataset management tools. The US base salary range for this full-time position is between $150,000 - $250,000 annually. The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended.

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About Snorkel At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data. We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes between 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!About the Role Snorkel AI is hiring Frontier AI Solutions Engineers who will partner with leading AI labs on their most challenging data problems. This is a high-impact, customer-facing role that combines technical depth with strong presales instincts. You'll partner with customer research teams to design complex data and environments that improve frontier model performance, demonstrating Snorkel's capabilities through research-driven engagements. You'll work at the critical intersection of research, technical strategy, and customer partnership. This includes scoping training data needs, designing RL environments and tasks, developing evaluation frameworks, probing model behavior and failure modes, and translating customer research objectives into actionable technical plans. You'll develop technical specifications, analyze frontier model failure modes, and serve as a thought partner to customer research teams throughout the sales cycle and into early delivery phases. Main Responsibilities Partner with frontier AI research labs to design datasets and environments that improve model performance Lead technical conversations with customer researchers to understand model capabilities, failure modes, data requirements, and success criteria Probe model behavior through systematic evaluation to uncover weaknesses and identify high-impact data interventions Design evaluation frameworks, calibration processes, and quality rubrics that establish measurable project success metrics Develop technical specifications for data projects that balance research rigor with operational feasibility Serve as thought partner to customer research teams throughout the sales cycle, building trust and credibility Stay current on frontier AI research, RL environment design, post-training techniques, and evaluation methodologies Preferred Qualifications Strong expertise in frontier AI concepts including LLMs, training data pipelines, evaluation methodologies, post-training techniques (RLHF, DPO, RLAIF), and domain areas such as coding agents, reasoning, multimodal models, or RL environments Experience in applied ML research, data science, or research-intensive technical roles with customer-facing or collaborative research experience Proficiency in Python and familiarity with ML frameworks and LLM APIs Excellent communication skills — ability to deliver technical presentations and explain complex concepts to diverse audiences Familiarity with data curation workflows, synthetic data generation, LLM-as-a-Judge, or evaluation framework design Ability to work in a fast-moving environment, comfortable with ambiguity and rapid iteration B.S. in Computer Science, Machine Learning, or related field with 4+ years of experience in AI/ML solutions engineering or technical customer-facing roles Compensation range for Tier 1 locations of San Francisco Bay Area and New York City, $172K - $300K OTE. All offers also include equity in the form of employee stock options. Our compensation ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Why Join Snorkel AI? At Snorkel AI, we're building the future of data-centric AI. Our Expert Data-as-a-Service organization partners with world-class customers to solve some of the hardest data challenges — creating training and evaluation data that power the next generation of LLMs and AI systems. You'll work directly on projects that impact real production systems, while shaping how internal teams deliver faster, better, and more intelligently. This is a rare opportunity to own technical data workflows and be a founding member of the technical DaaS team.  #LI-CG1 Salary Range  -   Salary Range $172,000—$300,000 USDBe Your Best at Snorkel Joining Snorkel AI means becoming part of a company that has market proven solutions, robust funding, and is scaling rapidly—offering a unique combination of stability and the excitement of high growth. As a member of our team, you’ll have meaningful opportunities to shape priorities and initiatives, influence key strategic decisions, and directly impact our ongoing success. Whether you’re looking to deepen your technical expertise, explore leadership opportunities, or learn new skills across multiple functions, you’re fully supported in building your career in an environment designed for growth, learning, and shared success. Snorkel AI is proud to be an Equal Employment Opportunity employer and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. Snorkel AI embraces diversity and provides equal employment opportunities to all employees and applicants for employment. Snorkel AI prohibits discrimination and harassment of any type on the basis of race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local law. All employment is decided on the basis of qualifications, performance, merit, and business need. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.