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Who We AreOver the next few years, every financial institution will have teams of AI analysts working alongside their sharpest minds. Agents have already reshaped software engineering. The same shift is coming for financial services.At Endex, we're building the most sophisticated AI coworker for finance. We're a team working at the frontier of agentic development and applied finance, in close collaboration with leading research labs and backed by OpenAI ($14M raised in Aug. 2025).With significant demand after our launch, the world’s largest financial firms recognize agentic financial modeling is the future.About the RoleLocation: New York City Commitment: 5 Days In-PersonWe're looking for engineers who want to work on category-defining AI work. Building agents with the performance and reliability Wall Street demands is one of the hardest applied AI problems out there.Our technical staff works across the stack: agent architecture, evals, model post-training, and new product surfaces. You'll ship to the largest financial firms in the world.Example Projects Include…Design and ship the core agentic systems that power Endex across planning, tool use, memory, long-horizon task execution.Partner with customers to understand finance workflows, and leverage learnings to improve our productBuild the evals, datasets, and post-training pipelines that turn raw model capability into a product analysts trustAs one of our earliest engineers, you'll shape our architecture, our hiring bar, and the engineering cultureYou may be a fit ifYou have architected and built scalable systemsYou have worked on agentic products or infrastructure and have informed opinions on reliability and performance of complex multi-step systemsYou have deep experience with API design, service communication patterns, and database optimizationYou have an iterative mindset where you develop proof of concepts, make decisions quickly, and ship v0sYou have strong software engineering fundamentals and enjoy owning the full lifecycle of production servicesFull-Time BenefitsHealth & Dental InsuranceMonthly Wellness Stipend401K MatchingCompetitive Salary + Equity

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About the Role: This role is part of our Maker Program, an 18-month rotational experience designed for early-career talent looking to build foundational skills across marketing, creative, and consumer-facing functions. As an AI Campaign Manager, you'll join our Growth Marketers and obsess over using artificial intelligence to manage and scale the entire campaign workflow for both B2C and B2B. In this role, you will build and maintain AI agents that automate workflows, analyze data, and enhance the speed at which we operate. This is a unique opportunity to work on a wide range of impactful projects as part of a broader rotational program within the marketing organization. What You'll Do: Design and build AI agents, using leading AI models and frameworks (Cursor, Claude, Gemini etc) to automate operational workflows and optimize initiatives across B2C and B2B channels Manage AI agents to continually enhance capabilities in data ingestion, analysis, and recommendation workflows Integrate with platform APIs across social and CTV to automate trafficking, tagging, naming, and reporting Partner closely with Growth Marketing, Creative, and Marketing Data Science teams to ensure creative assets ship quickly and are optimized post launch Evaluate emerging AI tools, models, and workflow frameworks, and apply them where they can meaningfully improve speed, quality, or scale Help establish best practices for how AI is used across the marketing organization Your Background: Up to three years of combined professional experience, including internships; recent graduates welcome Strong technical foundation, with experience in Python and/or JavaScript for automation, scripting, or lightweight application development Comfortable working with APIs, structured data, and workflow automation Comfort working in languages commonly used for automation — Python and/or JavaScript — or a clear appetite to learn quickly Familiarity with social platform ad managers (Meta, TikTok, Google, etc.), campaign trafficking, or ad tech is a plus Exposure to CTV/OTT, programmatic buying, or marketing APIs is a plus Technical degree in computer science, engineering, data science, information systems, or a related field is preferred, but not required  Program Eligibility Requirements: Application Deadline: May 15, 2026 Program Timeline: Minimum 18-month commitment, starting Aug 2026, after which successful participants will transition into non-rotational full-time roles Work Schedule: Full-time, hybrid in Los Angeles with office day requirements. Relocation assistance will not be provided. Work Authorization: Must have U.S. work authorization; we are unable to sponsor visas for this program Committed and available to work for the entire 18-month length of the program About the Program: The Tubi Makers Program offers an immersive journey through the Tubi Marketing and Creator ecosystems, blending hands-on project work with cross-functional rotations. Participants will join a cohort of new hires AKA Makers and gain a well-rounded perspective of how we connect with audiences by working alongside dedicated mentors and contributing to various departmental initiatives. By the end of the program, you will: Navigate diverse marketing and creator functions by rotating through different teams to see how an idea moves from a concept to consumer. Build a toolkit of skills through direct participation in real-time projects and team-based assignments, with a particular focus on building with AI tools. Expand your professional network by collaborating with mentors and peers across the organization to better understand Tubi’s unique brand culture. #LI-MJ1 #LI-Hybrid  Pursuant to state and local pay disclosure requirements, the pay range for this role, with final offer amount dependent on education, skills, experience, and location is listed per hour below. This role is also eligible for various benefits, including medical/dental/vision, insurance, a 401(k) plan, paid time off, and other benefits in accordance with applicable plan documents.  Hourly Rate for high cost labor markets such as but not limited to Los Angeles, New York City, and San Francisco$24.04—$24.04 USD Tubi is a division of Fox Corporation, and the FOX Employee Benefits summarized here, covers the majority of all US employee benefits.  The following distinctions below outline the differences between the Tubi and FOX benefits: For US-based non-exempt Tubi employees, the FOX Employee Benefits summary accurately captures the Vacation and Sick Time. For all salaried/exempt employees, in lieu of the FOX Vacation policy, Tubi offers a Flexible Time off Policy to manage all personal matters. For all full-time, regular employees, in lieu of FOX Paid Parental Leave, Tubi offers a generous Parental Leave Program, which allows parents twelve (12) weeks of paid bonding leave within the first year of birth, adoption, surrogacy, or foster placement of a child in addition to applicable government leave program(s) and FOX’s short-term disability policy. This time is 100% paid through a combination of any applicable state, city, and federal leaves and wage-replacement programs in addition to contributions made by Tubi. For all full-time, regular employees, Tubi offers a monthly wellness reimbursement. About Tubi: Boldly built for every fandom, Tubi is a free streaming service that entertains over 100 million monthly active users. Tubi offers the world's largest collection of Hollywood movies and TV shows, thousands of creator-led stories and hundreds of Tubi Originals made for the most passionate fans. Headquartered in San Francisco and founded in 2014, Tubi is part of Tubi Media Group, a division of Fox Corporation. We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, gender identity, disability, protected veteran status, or any other characteristic protected by law. We will consider for employment qualified applicants with criminal histories consistent with applicable law.

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The Perception Sensing team is looking for a Senior or Staff Software Engineer to drive the evaluation and architectural design of our PCP stack for future vehicle platforms enabling winter driving and low cost vehicle platforms. This team acts as the bridge between Perception Software and Autonomous Hardware Engineering (AHE). We ensure that as Zoox evolves toward future platforms, every sensor change across all modalities (Lidar, Radar, Camera etc) is validated with mathematical rigor. The role focuses on executing the technical validation pipeline and experimental design across the entire sensor suite.Responsibilities Execute the PCP metrics pipeline, assessing how hardware updates across various sensors impact PCP performance sensitivity in 3D scene understanding, live mapping and localization, especially in adverse weather and winter conditions. Design and run structured A/B testing experiments, including side-by-side custom mount runs and tandem vehicle data collection, to clear sensors for the winter ODD. Collaborate with AHE to correlate sensor-specific lab tests (e.g., heater/defroster impacts on camera lenses, snow accumulation on radomes) to downstream PCP performance. Root cause detection regressions to understand how early fusion models compensate for modality degradation in challenging environments. Design & develop performant and efficient multi-sensor fusion model to leverage the complementary advantage of on-board (low cost) sensors to improve Perception performance for highway and adverse weather. Qualifications Strong C++ and Python for running and modifying PCP metrics pipelines, automated testing, and re-simulations. Experience with A/B testing methodology (RBV - Risk Balanced Verification) for evaluating hardware/software changes in varied environments. Familiarity with diverse perception outputs and how environmental factors (like snow or fog) degrade bounding box precision/recall, point clouds, and 3D occupancy. Ability to define complex data collection plans for winter ODDs (e.g., specific snow types, ice, low temperatures). Experience with designing, developing and deploying multi-modality fusion based Perception models for 3D object detection, 3D segmentation & occupancy, Mapping and Localization.  Bonus Qualifications Experience in performance optimization to fit complex ML stack to low-power low cost edge compute (e.g., Nvidia Thor, TensorRT optimization). Experience with designing better sensor or better ML model for an anomaly or rare event/objects detection 242,000 - 333,000 a year

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Everyone's talking about AI. But here's the truth: ChatGPT can't send your emails. It can't book your flights. It can't even order you lunch.Why? Because AI is trapped in a chat box. It can't take real actions in the real world. We are changing that forever. We're not just building another AI company - we're creating the infrastructure that will power every AI application you'll use in the future. The Revolution Needs YouEvery AI app needs agentic "tools" - special functions that let AI models take real actions. Without tools, AI can only chat. With tools, AI can actually do things. We're building the definitive tools catalog and tool-calling platform that will unlock AI's true potential.  Think Zapier for AI Actions. Think Auth0 for AI. Think really big. Why This Is The Opportunity of a LifetimeFounder-Market Fit : Our CEO previously founded Stormpath (acquired by Okta), where he created the first Authentication API for developers. He's done this before - and this time the market is 10x bigger. Our CTO led the vector database team at Redis, shipped 100+ LLM applications, and is a contributor to LangChain and LlamaIndex. He knows this space better than anyone. Dream Team : We've assembled authentication, integrations, distributed systems, and AI experts from Okta, Redis, Microsoft, Splunk, Ngrok, Google, Airbyte, Disney, and HPE who've built and founded multiple successful developer platforms. Perfect Timing : We're at the inflection point of AI adoption. The biggest problem isn't better models - it's connecting AI to real-world actions. That's us.Massive Market : We're building critical infrastructure for the biggest technological shift of our generation. Every AI app will need what we're building.Backed By The Best: Our investors have backed Databricks, Clickhouse, MongoDB, Perplexity, Cohere, ScaleAI, Confluent, Elastic, and Firebase. They see what we see - this is going to be huge. The ChallengeWe are building the runtime and registry for AI/LLM tools.  You will define both how AI interacts with the world, and how humans build and manage those tools. This includes creating production-grade integrations, and the services & toolkits that run them... and the solving the unique problems of AI/LLM usage along the way.  We are building a SaaS application first, and then allowing folks to run part of that infrastructure on-site via hybrid deployments. This role is primarily focused on our back-end services, but as an early member of a startup, you’ll be working up-and-down the stack.  We build our software with Go, Python, and Typescript, and expect you to be a pro in at least one of those. We are looking for people who constantly ship and don't get stuck - we are looking for folks who are always learning and and able to apply that knowledge to their work and teach it to the team. What You'll DoBuild the infrastructure to manage the backplane for all future AI toolsDesign, build, test, and deploy high-performance, secure, production-grade software.Develop SDKs and frameworks that make it easy for other developers to build custom toolsHelp set industry standards for tool calling and authorization (for example, we helped write the MCP authorization spec)Create integrations with major platforms and LLMs (Google Workspace, Microsoft 365, OpenAi, Anthropic, etc.)Shape the roadmap for the teamBuild leverage (via AI) - projects that take a week today should take a day next time. Share your work with our customers and community, building our (and your) brand. Required SkillsAn insatiable desire to ship.7+ years of software engineering experience comprising of:5+ years of backend development experience with either Python, Go, Ruby, Typescript, or a similar language and API & Web frameworks.2+ years of experience with infrastructure and deployment (AWS/GCP, Terraform, Helm, etc)Strong experience building and maintaining production APIs.Track record of writing clean, well-documented, well-tested code.User-centered approach to designing developer-centric products and tools. Bonus PointsExperience building developer tools or SDKsFamiliarity with LLMs and AI frameworks (Langchain, LlamaIndex, etc)Open-source contributionsExperience with high-scale distributed systemsExperience leading teams and mentoring more junior developersFamiliarity with Typescript and a relevant frontend framework (e.g. React) You’ve been a startup founder or early-state startup employee before and love itNotes:This is an in-person role located in our San Francisco (SOMA) office. Join The MovementWe're not just building a product - we're leading a movement to transform AI from just chatbots to agents that can take actions against real systems. This is your chance to be at the forefront of that revolution. If you want to look back in 5 years and say, "I helped build that", then we want to talk to you. Ready to make AI actually useful? Apply Now

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Chef Robotics is on a mission to accelerate the advent of intelligent machines in the physical world, starting with food. We build AI-powered robots that assemble fresh meals at scale for some of the largest food producers in North America — companies making ready-to-eat meals for airlines, retailers, meal kits, and the frozen food aisle. Our robots operate in high-mix, high-variability production environments where ingredients change shape, color, and consistency from one tray to the next. Solving this requires tightly coupled perception, manipulation, and learning — and a team that ships hardware-software systems into customer facilities and keeps them running.  Headquartered in San Francisco, we are a venture-backed team of robotics, ML, and operations engineers building the foundation for general-purpose food robotics.About the Role Chef Robotics is building autonomous robots that work alongside humans in commercial food preparation environments — and perception is at the heart of what makes them reliable. As a Perception Engineer, you will own the full stack of how our robots see and understand the world: from integrating cutting-edge camera hardware, to training production-grade deep learning models, to ensuring those models perform accurately and efficiently in real-time on the factory floor.   You will work on some of the most technically rich problems in applied robotics — dense instance segmentation of deformable food items, real-time inference under tight latency constraints, sensor fusion, and robust tracking in cluttered, dynamic environments. You will not just train models; you will design the pipelines that gather and curate data, define the architectures that balance accuracy and speed, and own the deployment and field troubleshooting of what you build.   We are a small, high-ownership team. We work onsite five days a week and move with startup urgency — you will be expected to go deep technically while staying pragmatic about what ships.In this role, you will: Design, train, and optimize deep learning models for detection, segmentation, segmentation, pose estimation, and classification — with a focus on real-world robustness over benchmark performance. Build low-latency inference pipelines that approach real-time performance; profile and optimize models for deployment on embedded and edge hardware. Develop and improve multi-object tracking algorithms for reliable identification and motion prediction of items across frames. Solve challenging perception problems specific to food robotics: deformable objects, occlusions, varying lighting, and high visual similarity between categories. Own the end-to-end ML lifecycle: data collection strategy, annotation tooling, dataset curation, augmentation pipelines, model training, evaluation, deployment, and field debugging. Develop tooling to monitor model performance in production and drive continuous improvement cycles. Partner closely with robotics, hardware, and software engineers to translate perception capabilities into reliable end-to-end robot behaviors. Help define the perception roadmap and influence technical direction as the team grows. Assist in integrating new cameras and sensors for enhanced robotic vision. What You Bring: BS, MS, or PhD in Computer Science, Robotics, Electrical Engineering, or a closely related field. 5+ years of combined research and industry experience in computer vision and machine learning, with a track record of shipping perception systems to production. Deep expertise in at least two of: instance/semantic segmentation, object detection, 3D perception, or multi-object tracking. Strong Python skills; experience building production-quality, maintainable code — not just research prototypes. Hands-on experience with deep learning frameworks (PyTorch strongly preferred) and the full training pipeline from data to deployed model. Experience working with RGBD sensors, depth cameras, and point cloud data. Proven ability to build and optimize models for low-latency, real-time inference. Familiarity with ROS or similar robotics middleware. Nice-to-have: Experience using simulation environments (e.g. Isaac Sim, Gazebo) for synthetic data generation, domain randomization, and sim-to-real transfer of perception models. C++ proficiency for performance-critical modules and embedded deployment. Experience with cloud ML infrastructure (GCP, AWS) and containerization (Docker, Kubernetes). Background in autonomous vehicles, warehouse robotics, or other perception-heavy robotics applications. Contributions to open-source CV/ML projects or publications in top-tier venues (CVPR, ECCV, NeurIPS, etc.). 170,000 - 240,000 a year Chef is an early-stage startup where equity is a major part of the compensation package. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training.   In addition to salary and early-stage equity, we offer a comprehensive benefits package that includes medical, dental, and vision insurance, commuter benefits, flexible paid time off (PTO), catered lunch, and 401(k) matching.

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Chef Robotics is on a mission to accelerate the advent of intelligent machines in the physical world, starting with food. We build AI-powered robots that assemble fresh meals at scale for some of the largest food producers in North America — companies making ready-to-eat meals for airlines, retailers, meal kits, and the frozen food aisle. Our robots operate in high-mix, high-variability production environments where ingredients change shape, color, and consistency from one tray to the next. Solving this requires tightly coupled perception, manipulation, and learning — and a team that ships hardware-software systems into customer facilities and keeps them running.  Headquartered in San Francisco, we are a venture-backed team of robotics, ML, and operations engineers building the foundation for general-purpose food robotics.About the Role   As a Staff Autonomy Engineer, you will own the technical architecture of Chef's autonomy stack end-to-end — from perception and action prediction through closed-loop control and production deployment. This is a hands-on technical leadership role: expect to spend the majority of your time designing and building, with the remainder setting direction, mentoring engineers, and driving cross-functional alignment. You will report directly to the engineering leadership and have direct influence over how Chef's autonomy systems scale across a growing commercial fleet.   We are a small, high-ownership team. We work onsite five days a week and move with startup urgency.  In this role, you will: Own the end-to-end architecture and hands-on development of Chef's autonomy stack — perception, action prediction, closed-loop control, and sensor fusion — from prototype through production deployment Design and implement learning-based systems that predict and execute robot actions from visual and operational observations, generalizing across diverse ingredient types with minimal per-item tuning Build closed-loop control systems that integrate vision, weight feedback, force-torque sensing, and trajectory planning for robust real-world manipulation Develop rapid onboarding capabilities — algorithms and tooling that enable new meal types and ingredient configurations to be deployed quickly from minimal demonstrations Instrument autonomy systems for production monitoring, failure detection, and continuous improvement; build data collection pipelines that feed back into model retraining Define objective qualification criteria for autonomy subsystems; drive reliability and performance improvements using production data across the deployed fleet Investigate and integrate the latest advances in robot learning, foundation models, and manipulation research — continuously evaluating what's ready to move from research into production Mentor senior engineers, lead design reviews, and help build a team capable of scaling Chef's autonomy stack to hundreds of deployed systems What You Bring: Demonstrated experience shipping a complete autonomy or manipulation system to real-world deployment — not just simulation or research prototypes Deep technical expertise across at least two of: perception systems, visuomotor control, action prediction, sensor fusion, or motion planning Strong software engineering fundamentals in Python and C++; experience building production-quality, maintainable systems across research and deployment codebases Track record of technical leadership: driving architecture decisions, leading cross-functional projects, and raising the engineering bar on a team Comfort with ambiguity and urgency — able to set direction and execute in a fast-moving startup environment Nice-to-have: Experience with food, agricultural, or consumer goods robotics where object variability is high Experience with ML frameworks (PyTorch preferred) and the full model lifecycle — training, evaluation, deployment, and field iteration Familiarity with foundation model approaches for manipulation: diffusion policies, VLAs, world models, JEPA-style architectures Background in sim-to-real transfer, domain randomization, or synthetic data generation for manipulation Experience with ROS and real-time robotics middleware Prior startup technical leadership experience 160,000 - 240,000 a year Chef is an early-stage startup where equity is a major part of the compensation package. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training.   In addition to salary and early-stage equity, we offer a comprehensive benefits package that includes medical, dental, and vision insurance, commuter benefits, flexible paid time off (PTO), catered lunch, and 401(k) matching.  

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About Cantina:Cantina Labs is a social AI company, developing a suite of advanced real-time models that push the boundaries of expression, personality, and realism. We bring characters to life, transforming how people tell stories, connect, and create. We build and power ecosystems. Cantina, our flagship social AI platform, is just the beginning.About the Role:Cantina is expanding, and we're looking for an ML Engineer to join our growing Singapore team! In this role, you will build and scale systems for ingesting, processing, and delivering large-scale video and multimodal data for model training. You'll own the full pipeline — from raw content to curated, filtered, and training-ready datasets — with a focus on speed, reliability, reproducibility, and cost-efficiency. You'll partner closely with curation and modeling teams to operationalize evolving dataset recipes and iterate on approaches that improve model outcomes.What You’ll Do:Design and scale distributed data pipelines for preprocessing, dataset generation, and repeated dataset refreshesOwn workflow orchestration, job scheduling, monitoring, and failure recovery for large-scale data processing jobsImplement and maintain containerized pipeline infrastructure using Kubernetes or equivalent orchestration systemsOptimize cloud-based data storage and movement across providers (AWS, GCS, or Azure) for cost, throughput, and operational efficiencyDefine and implement best practices for dataset storage layout, versioning, caching, retention, and access patternsDesign and implement curation pipelines that determine which video and image content is selected, filtered, and retained for model training, including image-text pair datasets used in joint training regimesBuild and improve VLM-based captioning and metadata generation workflows at scale across both video and image dataDevelop and apply quality and aesthetic scoring models, CLIP-based semantic filtering, and other signal-extraction approaches for data selectionBuild tooling to support deduplication workflows at scale, including near-dedup and exact deduplication pipelines over large video corporaAnalyze dataset composition, identify quality issues, and iterate on curation logic to improve training outcomesDefine and evolve standards for what constitutes high-quality, training-ready video data across different training regimesWhat You’ll Bring:Strong hands-on experience building or scaling large-scale data systems and pipelines for machine learning, including dataset curation, filtering, and quality improvementExperience with distributed data processing frameworks such as PySpark or Ray, and orchestration tools such as Airflow or equivalentFamiliarity with containerization and container orchestration, including Docker and KubernetesExperience working with cloud-based data storage and compute (AWS, GCS, and/or Azure), including tradeoffs around cost, throughput, storage layout, and access patternsExperience with VLM-based captioning pipelines or quality/aesthetic scoring models for video or image data, including curation of image-text pair datasets for joint image-video trainingFamiliarity with CLIP-based or embedding-based filtering and semantic data selection techniquesFamiliarity with video and media processing tools such as FFmpeg, PyAV, DALI, or OpenCV, and relevant libraries such as Decord, torchvision, PyTorchVideo, or torchaudioProficiency in PythonStrong problem-solving, communication, and documentation skillsBenefits We Offer:Competitive salary and generous company equityPersonal time off and paid holidaysHealth insuranceGlobal travel insurance: Covers you when traveling internationallyMonthly spending stipend: $500 (~S$635)Equipment: All equipment needed for your home office

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About Cantina:Cantina Labs is a social AI company, developing a suite of advanced real-time models that push the boundaries of expression, personality, and realism. We bring characters to life, transforming how people tell stories, connect, and create. We build and power ecosystems. Cantina, our flagship social AI platform, is just the beginning.About the Role:Cantina is expanding, and we're looking for a Research Scientist to join our growing Singapore team! In this role, you will drive foundational research on video generation models, taking ownership across the full research cycle and driving post-training research. Furthermore, you'll collaborate closely with data, infrastructure, and adjacent modeling teams to translate research findings into durable model improvements.What You’ll Do:Build and maintain scalable systems for ingesting, preprocessing, and delivering large-scale video data for model trainingDesign and scale distributed data pipelines for preprocessing, dataset generation, and repeated dataset refreshesOwn workflow orchestration, job scheduling, monitoring, and failure recovery for large-scale data processing jobsImplement and maintain containerized pipeline infrastructure using Kubernetes or equivalent orchestration systemsOptimize cloud-based data storage and movement across providers (AWS, GCS, or Azure) for cost, throughput, and operational efficiencyDefine and implement best practices for dataset storage layout, versioning, caching, retention, and access patternsBuild tooling to support deduplication workflows at scale, including near-dedup pipelines over large video corporaResearch and develop distillation methods for large-scale diffusion and flow-based video generation models, including guidance distillation and adversarial distillation, with a focus on preserving or improving generation quality while reducing inference costDevelop reward models and preference-based fine-tuning pipelines that align video generation quality with human judgments across dimensions such as aesthetics, motion quality, and prompt adherenceAnalyze the relationship between base model behavior and post-training outcomes, and work with the foundation model team to inform pretraining decisions accordinglyWhat You’ll Bring:Strong hands-on experience building or scaling large-scale data systems or pipelines for machine learning workflowsExperience with distributed data processing frameworks such as PySpark or Ray, and orchestration tools such as Airflow or equivalentFamiliarity with containerization and container orchestration, including Docker and KubernetesExperience working with cloud-based data storage and compute (AWS, GCS, and/or Azure), including tradeoffs around cost, throughput, storage layout, and access patternsFamiliarity with video and media processing tools such as FFmpeg, PyAV, DALI, or OpenCVFamiliarity with multimodal or media data, including video, image, text, and audioStrong research background in post-training methods for large-scale diffusion or flow-based generative models, with deep hands-on experience in distillation across both inference efficiency and quality preservationExperience with reward modeling or preference-based fine-tuning for generative models, including RLHF, DPO or equivalent alignment approachesSolid understanding of the interplay between pretraining and post-training, and how base model properties affect distillation and fine-tuning outcomesProficiency in Python and modern machine learning frameworks, with a strong preference for PyTorch or JAXTrack record of independent research, with the ability to drive projects from initial idea through experimental validationPublications at top-tier venues (NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV) preferredGood understanding of the practical challenges involved in building reliable, scalable, and reproducible data workflows for machine learning systemsBenefits We Offer: Competitive salary and generous company equityPersonal time off and paid holidaysHealth insuranceGlobal travel insurance: Covers you when traveling internationallyMonthly spending stipend: $500 (~S$635)Equipment: All equipment needed for your home office

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🚀 About MyriadWe are building a reliable and scalable AI-powered platform that allows US companies to put regulatory compliance on autopilot.At its core, Myriad is an engineering-driven company, founded by individuals with robust technical backgrounds, forged in Silicon Valley and molded by necessity.Myriad's software engineers are at the forefront of developing next-generation technologies that revolutionize the way enterprises manage their compliance.We employ individuals with a diverse range of technical abilities who are eager to address some of the most challenging issues in technology and create a significant impact on users worldwide. Our engineering and legal engineering teams come from reputable companies: ❓Why compliance?Compliance isn’t just about regulations and checkboxes—it’s the foundation of trust, stability, and ethical progress in our global economy. It safeguards financial systems from fraud, protects consumers from exploitation, and ensures businesses operate with integrity.In fintech, compliance is a catalyst for innovation. It enables secure digital transactions, prevents money laundering, and fosters financial inclusion by ensuring that emerging technologies remain safe and accountable. From AI-driven risk monitoring to real-time fraud detection, compliance empowers businesses to scale responsibly while protecting society from financial crime. At its core, compliance is about fairness, security, and trust—paving the way for a more transparent and ethical financial future. It’s not just a regulatory requirement; it’s a force for good, shaping a world where businesses thrive while protecting people and institutions alike.💸 We are backed by top US and EU venture capital with several years of runway - Arielle Zuckerberg (Long Journey VC) and Tom Preston-Werner (Github founder) invested in us, just to name a few...Read more about us on cc.cz and hn.cz🤗 What we offerYou can be a part of the core engineering team of a newly created and VC-backed startupSilicon Valley-style company => stock options and/or RSUs!Steep career growth opportunities through continuous growth and our Silicon Valley pedigreeTechnical Founders (experience from Google, Google X - The Moonshot Factory, Amazon, BMW, Airbnb, Dropbox, NVIDIA)Competitive salary and benefitsPrague and San Francisco offices, we are a multi-homed company with a hybrid approach to work (biz travel to Silicon Valley)Paid Time Off (Vacation, Sick & Public Holidays)Flat hierarchies and open feedback cultureRalf and Jan, Myriad AI founders. 🎉 About YouYou contribute fresh perspectives in a variety of domains, including information retrieval, distributed computing, large-scale system design, networking, data storage, security, artificial intelligence, and natural language processingYou know how to design, develop testing, deploy, maintain, and enhance software solutionsYou are comfortable managing project priorities, deadlines, and deliverables, and demonstrate leadership capabilitiesYou are eager to address some of the most challenging issues in technology and create a significant impact on users worldwideYou love being mission driven and want to join an early stage Silicon Valley based startup👨‍🔬 About the roleAs the Senior AI Engineer, you will play a pivotal role in shaping the AI strategy and architecture of our cutting-edge fintech compliance platform..In this role, you’ll design and deploy scalable machine learning models, oversee model governance and explainability, and work closely with cross-functional teams to integrate AI seamlessly into our platform. You’ll also set technical direction, mentor a growing AI team, and ensure our AI solutions meet the highest industry standards for accuracy, fairness, and compliance.This is an opportunity to lead AI innovation in compliance, solving complex challenges with cutting-edge techniques in NLP, anomaly detection, and automated reporting. If you're passionate about AI’s role in transforming financial security and compliance, we’d love to hear from you!👨‍🔬 In this role you willHelp design AI Strategy & Development – Define and drive the AI roadmap for our compliance platformEnsure Model Explainability & Compliance – Develop transparent and interpretable AI solutions that meet regulatory standardsCollaborate Cross-Functionally – Work with engineers, data scientists, and compliance experts to integrate AI into the platformOptimize AI Performance – Improve model accuracy, efficiency, and scalability in a high-stakes financial environmentStay Ahead of AI Trends – Research and implement the latest advancements in AI, NLP, and anomaly detectionMentor & Guide the Team – Be the lead and mentor a growing AI team, fostering a culture of innovation and excellenceDrive AI Governance & Ethics – Establish best practices for bias mitigation, model validation, and responsible AI use 📖 Minimum qualificationsBachelor’s degree or equivalent practical experience2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree in an industry setting2 years of experience with data structures or algorithms in either an academic or industry setting2 years of experience with machine learning algorithms and tools (e.g., TensorFlow), artificial intelligence, deep learning or natural language processing 📖 Preferred qualificationsMaster's degree or PhD in Computer Science or related technical field3 years of experience with performance, large scale systems data analysis, visualization tools, and/or debugging3 years of experience with machine learning algorithms and tools (e.g., TensorFlow), artificial intelligence, deep learning or natural language processingProficiency in code and system health, diagnosis and resolution, and software test engineering2 years of experience with LLMs and training ❗ Important ❗Before applying for this position please check out the following questionnaire and make sure that you are comfortable answering these questions without using of any external sources (feel free to submit the answers too). You will be tested on both your theoretical and your practical knowledge of ML/AI, LLMs.Note 1: previous work references might be required.Note 2: ChatGPT-generated applications will be automatically rejected.

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Research Engineer — EvalsLocation: San Francisco, CA (Hybrid) OR Remote (Americas, UTC-3 to UTC-10) Employment Type: Full time Department: Engineering Team Compensation: $160K – $240K • 0.01% – 0.10%OverviewYou'll build the evaluation systems that tell us whether Firecrawl actually works. That sounds simple. It isn't. Our core promise — convert any URL into clean, structured, LLM-ready data reliably — is hard to measure rigorously across millions of different websites, formats, and edge cases. As we layer in models and agent workflows, the question "did that work?" gets harder, not easier.This isn't an eval role where you inherit a framework and run benchmarks. You'll design the metrics, build the pipelines, generate the datasets, and own the feedback loop from output quality back to model and product decisions. If you care about what "good" actually means and have the engineering depth to measure it, this is the role. Salary Range: $160,000 to $240,000/year (Range shown is for U.S.-based employees in San Francisco, CA. Compensation outside the U.S. is adjusted fairly based on your country's cost of living.)Equity Range: Up to 0.10%Location: San Francisco, CA or Remote (Americas, UTC-3 to UTC-10)Job Type: Full-TimeExperience: 3+ years in ML engineering, applied AI, or data quality — with production systemsVisa: US Citizenship/Visa required for SF; N/A for RemoteAbout FirecrawlFirecrawl is the easiest way to extract data from the web. Developers use us to reliably convert URLs into LLM-ready markdown or structured data with a single API call. In just a year, we’ve hit millions in ARR and 50k+ GitHub stars by building the fastest way for developers to get LLM-ready data.Previously, we built Mendable, one of the first commercially available “chat with your data” applications. We sold to companies like MongoDB, Coinbase, Snapchat, and more. To do this, we spent a surprising amount of time building reliable infrastructure for getting clean data from the web. When we started to see our founding friends rebuilding the same thing, we thought we might be on to something.Why FirecrawlTechnical ownership – Lead critical browser technology and infrastructureReal impact – Directly shape how our browser stack drives our entire productHigh velocity – Rapid iteration and deployment of your workSmall team, big ambition – Collaborate closely with founders, influencing key decisions and future directionsWhat You’ll DoBuild the eval stack from scratch. Design and own the systems that measure whether Firecrawl's outputs are actually good — across scrape, crawl, extract, and map. That means defining metrics, building pipelines, curating datasets, and integrating evals into CI/CD so regressions get caught before they ship. You build the infra yourself because you're the one who needs it to work.Design benchmarks that reflect reality. Our outputs need to hold up across millions of websites — SPAs, paywalled content, dynamic rendering, structured and unstructured formats. You'll build benchmark datasets that cover the real distribution of what our customers send us, including the edge cases that break naive approaches. Ground truth doesn't come for free — you'll design the collection and labeling systems too.Own LLM-as-judge pipelines. You'll design and validate automated judges that score extraction quality at scale, know the failure modes of LLM-based evaluation, and build the human review tooling needed when automation isn't enough. You understand the difference between an eval that measures something real and one that just flatters the system.Close the loop with models and RL. Evals here aren't a reporting layer — they're a training signal. You'll work closely with the RL and Search/IR research engineers to turn quality measurements into reward signals and feedback loops that make models meaningfully better. Your benchmarks directly influence what gets trained next. Run fast experiments and communicate clearly. You design experiments that test meaningful hypotheses, run them quickly, and make decisions based on results. When you have findings, anyone on the team can understand what they mean — no decoder ring required.What We're Looking ForBuilds their own eval infrastructure. You don't wait for tooling to appear. You write the pipelines, curate the datasets, design the rubrics, and validate the judges yourself — because you understand that infra choices directly affect what you're actually measuring. You've run evals at scale and debugged the places where they lie.Knows what "good" means for unstructured web data. You've worked with messy, real-world data before. You understand why markdown quality is hard to define, why structured extraction fidelity varies by schema, and why naive string-match metrics miss the point. You have strong opinions about what a useful benchmark actually looks like — and the rigor to validate them.Fluent in LLM evaluation methodology. You understand LLM-as-judge systems, their correlation with human judgment, and where they break down. You've designed rubrics that hold up under adversarial inputs, built human review pipelines that scale, and know how to measure inter-rater agreement. You're not fooled by evals that only look good in aggregate.Production-minded. You care about whether your evals reflect real production behavior, not just offline benchmarks. You've worked on systems serving real traffic and made hard tradeoffs between evaluation depth, coverage, and cost. A benchmark that doesn't represent what customers actually send isn't a benchmark worth maintaining.Fast and clear. You'd rather run three rough experiments this week than one polished one next month. When you have results, anyone on the team can understand what they mean — and what to do next.Backgrounds that tend to do well: ML engineers who've built eval or data quality systems at AI labs or applied teams. Engineers who've worked on LLM fine-tuning or RLHF pipelines and understand how feedback quality drives model improvement. People who've worked at the intersection of data infrastructure and model development. Anyone who's been the person on the team asking "but how do we know this actually works?" What We're NOT Looking ForBenchmark runners. If your eval experience is running existing frameworks on existing benchmarks and reporting numbers, this isn't the right fit. We need someone who builds the frameworks and defines the benchmarks.People who treat evals as an afterthought. If your default workflow is to build first and evaluate later — or to treat pass rates as a proxy for actual quality — you'll struggle here. Evals are a first-class product, not a QA gate.Researchers who need a platform team. If you expect pipelines, datasets, and labeling infrastructure to exist before you can be productive, you'll be frustrated. You build the tools you need. Slow iterators. If your standard experiment cycle is measured in weeks, not days, you'll struggle with the pace. We need someone who can design, run, and interpret a meaningful experiment within a day or two.Bonus PointsAny other niche expertise and skills Previous experience at a scraping, automation, or security-focused startupEx-founderWhat it Means to Join FirecrawlHigh Leverage — Your processes directly amplify our growth.Autonomy — Own your domain; we care about outcomes, not hours.Remote-First Culture — Work at our new SF office, while collaborating with our remote team.Growth Opportunity — Early equity and a role that scales with the company.Creative Freedom — Experiment with new channels, formats, and automations. If it works, we run with it.Benefits & PerksAvailable to all employeesSalary that makes sense — $140,000-180,000/year (U.S.-based), based on impact, not tenureOwn a piece — Up to 0.15% equity in what you're helping buildUnlimited PTO — Minimum 3 weeks off encouraged; take the time you need to rechargeParental leave — 12 weeks fully paid, for moms and dadsWellness stipend — $100/month for the gym, therapy, massages, or whatever keeps you humanLearning & Development - Expense up to $150/year toward anything that helps you grow professionallyTeam offsites — A change of scenery, minus the trust fallsSabbatical — 3 paid months off after 4 years, do something fun and newAvailable to US-based full-time employeesFull coverage, no red tape — Medical, dental, and vision (100% for employees, 50% for spouse/kids) — no weird loopholes, just care that worksLife & Disability insurance — Employer-paid short-term disability, long-term disability, and life insurance — coverage for life's curveballsSupplemental options — Optional accident, critical illness, hospital indemnity, and voluntary life insurance for extra peace of mindDoctegrity telehealth — Talk to a doctor from your couch401(k) plan — Retirement might be a ways off, but future-you will thank youPre-tax benefits — Access to FSAs and commuter benefits to help your wallet out a bitPet insurance — Because fur babies are family tooAvailable to SF-based employeesSF HQ perks — Snacks, drinks, team lunches, and the occasional burst of chaotic startup energyInterview ProcessApplication Review – Send us your stuff, and a quick note on why you're excitedAutomated Assessment (~30 min) - We will do an initial automated assessment of your skills and knowledge.Intro Chat (~25 min) – Quick alignment call with a member of our teamTechnical Interview (~1 hr) – Tackle a small challengeInterview with Founders (~30 min) – Culture, vision, and long-term fitPaid Work Trial (1–2 weeks) – Work on something real with usDecision – We move fastIf you’ve ever wanted to own a product-critical system and build alongside founders, this is your moment. Apply now and let’s talk.

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About KodiflyKodifly is an AI-first spatial intelligence company transforming infrastructure monitoring and management. Headquartered in Hong Kong Science Park, with an expanded presence in Pakistan and ongoing expansion into the Kingdom of Saudi Arabia, we are backed by HKAI Lab and the NVIDIA Inception program.Our expertise spans 3D point cloud processing, digital twin creation, and LiDAR technology. By integrating AI-powered analytics, digital twins, and real-time spatial intelligence, we help cities and enterprises improve efficiency, quality assurance, and safety across the infrastructure lifecycle.Job DescriptionWe are looking for a Senior Computer Vision & Robotics Engineer with 4+ years of hands-on experience in 3D perception and spatial data processing. This role requires strong individual contribution, real project ownership, and the ability to work on production-facing systems.You will be responsible for building, improving, and optimizing SLAM (Simultaneous Localization and Mapping), 3D vision, and spatial AI pipelines, while collaborating closely with teams in Pakistan and Hong Kong.Key ResponsibilitiesDesign and implement algorithms for 3D point cloud processing, object detection, and segmentationEnhance and optimize SLAM pipelines for real-time mobile and static environmentsWork on camera–LiDAR calibration and multi-sensor data alignmentApply deep learning techniques to 2D, 3D, and spatial dataIntegrate and optimize tools such as Open3D and 2D+3D inference models into existing systemsOptimize computer vision models and pipelines for NVIDIA GPUsPerform profiling and performance optimization to improve latency and accuracyCollaborate with cross-functional teams across Pakistan and Hong Kong to deliver product featuresParticipate in R&D to evaluate new computer vision and robotics techniquesEnsure robustness and reliability of computer vision systems in real-world conditionsSupport and guide junior engineers through reviews and technical discussionsQualifications4+ years of hands-on experience in computer vision or roboticsBachelor’s, Master’s, or PhD in Computer Science, Engineering, or a related fieldStrong experience with 3D point clouds, SLAM, and sensor calibrationHands-on experience applying deep learning to vision and spatial dataProficiency in Python and C++Experience with PyTorch or TensorFlowPractical experience optimizing models for NVIDIA GPUsFamiliarity with CUDA, cuDNN, or TensorRT is a plusExperience with OpenCV, Open3D, or PCLUnderstanding of computer vision fundamentals (detection, segmentation, tracking)Experience with ROS or robotics workflowsStrong problem-solving skills and ability to work independentlyGood communication skills and a collaborative mindsetWhat We OfferWork on cutting-edge 3D vision and spatial intelligence systemsExposure to real-world infrastructure and robotics use casesCollaborative and growth-focused engineering environmentCompetitive salary and equity optionsFast-track growth opportunities for high performersJoin UsIf you have solid hands-on experience in computer vision and robotics, enjoy solving complex spatial problems, and want to build real-world AI systems, we’d love to hear from you.🚀 Apply now and grow with Kodifly.

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Ironclad is the leading AI contracting platform that transforms agreements into assets. Contracts move faster, insights surface instantly, and agents push work forward, all with you in control. Whether you’re buying or selling, Ironclad unifies the entire process on one intelligent platform, providing leaders with the visibility they need to stay one step ahead. That’s why the world’s most transformative organizations, from Rivian to the World Health Organization and the Associated Press, trust Ironclad to accelerate their business. We’re consistently recognized as a leader in the industry: a Leader in the Forrester Wave and Gartner Magic Quadrant for Contract Lifecycle Management, a Fortune Great Place to Work, and one of Fast Company’s Most Innovative Workplaces. Ironclad has also been named to Forbes’ AI 50 and Business Insider’s list of Companies to Bet Your Career On. We’re backed by leading investors including Accel, Y Combinator, Sequoia, BOND, and Franklin Templeton. For more information, visit www.ironcladapp.com or follow us on LinkedIn. This is a hybrid role. Office attendance is required at least twice a week on Tuesdays and Thursdays for collaboration and connection. There may be additional in-office days for team or company events.Engineering @ IroncladAs a Senior Staff Software Engineer at Ironclad, you'll work cross-functionally to identify business problems and architect, build, and verify solutions. You'll build a platform that lets lawyers scale themselves and their businesses 100x more effectively. At Ironclad, we’ve built a product that brings a two thousand year old profession into the digital age, and you’ll play a pivotal role in driving the foundation forward by building the wave of AI powered contract intelligence features.We seek experienced engineers with strong coding fundamentals and a track record of shipping high quality products. We work in a highly collaborative environment, and strive to foster a positive, inclusive culture and offer remote work flexibility. If you’d like to join us on our mission to build the product that legal teams love, let’s talk!What you'll do:Serve as the Technical Lead Architect and owner of Ironclad’s document and record service, driving the technical strategy and decisions that ensure reliability, scalability, and performancePartner across engineering teams, ensuring the document service unlocks new feature capabilities and AI innovationMentor and provide thoughtful feedback to other engineers and cultivate a culture of engineering excellenceCollaborate cross functionally with product managers, designers, and other engineers to spec, design, and build features and systemsPartner with quality engineers to define, build and maintain testing strategyGrow your teams by interviewing and recruiting talented engineers to IroncladWork on a modern stack built upon: TypeScript, Node.js, PostgresSQL, Temporal, and Docker containers in Kubernetes on Google Cloud Platform (experience with these specific technologies not required)Build and apply AI tools and features to power the future of contract intelligenceWhat we look for:At least 7 years of software experience architecting, building, launching and maintaining complex (backend/platform) systems (a formal degree is not required, we are prioritizing industry experience)Leadership across teams and a drive towards improving overall technical architecture and achieving company-wide goalsPassion for software engineering to build and ship great productExperience leveraging AI tooling across a team to improve execution quality and velocityHands-on experience shipping valuable products to production with real user feedbackA high bar for qualityStrong cross-team communication and collaboration skillsIronclad’s Values: drive, intent, integrity, and empathyBase Salary Range: $250,000 - $270,000The base salary range represents the minimum and maximum of the salary range for this position based at our San Francisco headquarters. The actual base salary offered for this position will depend on numerous factors, including individual proficiency, anticipated performance, and the location of the selected candidate. Our base salary is just one component of Ironclad’s competitive total rewards package, which also includes equity awards (a new hire grant, along with opportunities for additional awards throughout your tenure), competitive health and wellness benefits, and a commitment to career growth and development. US Full-Time Employee Benefits at Ironclad:100% health coverage for employees (medical, dental, and vision), and 75% coverage for dependents with buy-up plan options availableMarket-leading leave policies, including gender-neutral parental leave and compassionate leaveFamily forming support through Maven for you and your partnerPaid time off - take the time you need, when you need itMonthly stipends for wellbeing, hybrid work, and (if applicable) cell phone useMental health support through Modern Health, including therapy, coaching, and digital toolsPre-tax commuter benefits (US Employees)401(k) plan with Fidelity with employer match (US Employees)Regular team events to connect, recharge, and have funAnd most importantly: the opportunity to help build the company you want to work at**UK Employee-specific benefits are included on our UK job postingsPursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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About the TeamOur Safety Systems team is at the forefront of OpenAI's mission to build and deploy safe AGI, driving our commitment to AI safety and fostering a culture of trust and transparency.Within Safety Systems, the Model Policy team aligns model behavior with desired human values and norms. We co-design policy with models and for models by driving rapid policy taxonomy iteration based on data and defining evaluation criteria for foundational models’ ability to reason about safety.About the RoleFrontier AI systems are rapidly expanding what is possible in cybersecurity and software engineering. These capabilities create major defensive opportunities, but they also raise serious dual-use and misuse risks across areas such as malware development, exploit discovery, vulnerability chaining, credential abuse, cyber intrusion, and autonomous offensive operations.In this role, you will help define how OpenAI’s models should behave in high-risk cybersecurity contexts. You will develop policy frameworks, threat models, taxonomies, evaluations, and behavioral specifications that guide model behavior across training, deployment, and monitoring systems. This role sits at the intersection of cybersecurity, AI safety, threat modeling, evaluation science, and policy implementation.You will work closely with research, engineering, safety training, preparedness, and product teams to build policies that are technically grounded, measurable, enforceable, and responsive to real-world cyber risk.Your Responsibilities:Design and maintain model policies for cybersecurity and frontier-risk domains, especially dual-use and high-risk cyber capabilities.Translate cybersecurity threat models into clear behavioral specifications, evaluation criteria, grading guidance, and system-level mitigations.Define practical boundaries between legitimate security research, defensive workflows, and assistance that could materially enable harmful activity.Build policy artifacts that support implementation across training, evaluation, deployment, monitoring, and escalation systems.Partner with safety researchers, engineers, and evaluation teams to operationalize policies into scalable model behavior and measurable safeguards.Analyze red-teaming results, deployment data, model failures, over-refusals, and ambiguous edge cases to improve policy and evaluation quality over time.Identify emerging cyber capability areas where advanced AI systems could lower barriers to misuse or increase operational capability for malicious actors.Contribute to system cards, safety reports, policy documentation, and external communications on OpenAI’s approach to cyber risk mitigation.We’re Seeking:Strong technical expertise in cybersecurity, such as offensive security, defensive security, vulnerability research, malware analysis, incident response, threat intelligence, application security, exploit development, infrastructure security, or cloud security.Strong judgment about how AI systems may affect the cyber threat landscape, including dual-use, autonomous, or agentic system risks.Ability to distinguish between legitimate security use cases and assistance that could materially enable harmful cyber activity.Experience building or applying threat models to complex technical systems, especially in adversarial or high-risk environments.Ability to translate technical security expertise into structured policy frameworks, evaluation criteria, operational guidance, and enforcement mechanisms.Comfort using empirical evidence, including evaluations, red-teaming results, deployment observations, and model failure modes, to inform policy decisions.Strong systems thinking across policy, evaluations, classifiers, training, deployment safeguards, measurement, and monitoring.Ability to work cross-functionally with researchers, engineers, product teams, policy experts, and operational stakeholders.Strong written communication skills, especially the ability to explain complex technical and security concepts clearly.A pragmatic approach to safety: focused on reducing real-world risk while preserving legitimate, beneficial, and defensive uses of AI.Our relevant publications:Accelerating the cyber defense ecosystem that protects us allSafety at every stepSafety evaluations hubGPT‑5.5 System CardOpenAI Model SpecWorkplace & LocationThis role is based in our San Francisco office. We do encourage you to apply even if you prefer a different work location as factors may change over time.We offer relocation support to new employees, and we use a hybrid model: three days in the office per week with optional work from home on Thursdays and Fridays.Our open-plan offices have height-adjustable desks, conference rooms, phone booths, well-stocked kitchens full of snacks and drinks, three in-house prepared meals daily, a private outdoor space for working in the sun or socializing, nap rooms, private bike storage, and more.About OpenAIOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.OpenAI Global Applicant Privacy PolicyAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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About the TeamThe Alignment Oversight team at OpenAI develops techniques for improving control, accountability, and alignment as AI systems become more capable and agentic.We combine longer-horizon research with hands-on deployment. We study long-term questions about how increasingly intelligent systems can be supervised, constrained, and corrected, while also building oversight systems that are used in practice today, both internally and externally (see our recent work on code review and action monitoring for codex).We also study how to learn from real-world deployments: using oversight data and human interventions to train future models to be more aligned, while preserving the effectiveness and independence of the oversight systems themselves. About the RoleAs a researcher on the Alignment team, you will design and run experiments that improve our ability to oversee increasingly capable models. You will work on hands-on model training, evaluation design, and research infrastructure, and translating promising oversight ideas into systems that can operate on real model traffic and real user workflows.This role combines longer-horizon research with shorter deployment sprints, with projects typically scoped around 3-6 month research timelines and aimed at directly improving future model behavior.This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.In this role, you will:Design and implement alignment experiments focused on oversight systems for increasingly agentic AI models.Deploy practical systems for action monitoring, red-teaming, and human-in-the-loop control.Develop evaluations for alignment failure modes of the frontier models such as overeagerness, instruction following failures, covert actions, avoiding restrictions and scheming propensity.Analyze deployment data to understand model failures, oversight gaps, and opportunities for training more aligned models.Develop techniques for feeding oversight signals back into training while preserving the reliability and independence of the oversight process.Produce externally publishable research when results advance the broader science of alignment.Collaborate across research, product, security, safety, and engineering teams to turn alignment ideas into working systems.Move quickly from research intuition to working experiments, prototypes, and evidence that can shape future models.You might thrive in this role if you:Have strong hands-on experience training, evaluating, or debugging large ML models, especially LLMs.Have experience with reinforcement learning, post-training, preference optimization, scalable oversight, model evaluation, or adjacent empirical ML research.Have strong engineering execution and can turn ambiguous research ideas into reliable experiments, tools, training pipelines, and production-facing systems.Have research intuitions for what experiments are likely to teach us something, while staying grounded in implementation details and empirical results.Are a team player - willing to do a variety of tasks that move the team forward.Enjoy fast-paced, collaborative research environments where priorities shift as models and evidence change.See safety and usefulness as coupled goals.About OpenAIOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.OpenAI Global Applicant Privacy PolicyAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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About the TeamThe Codex Deployment Engineering team helps customers adopt OpenAI's coding tools throughout their software development lifecycle. We act as trusted technical partners, guiding engineering teams as they integrate Codex into their projects and workflows. Our customers span digital-native companies to global enterprises, and we work side-by-side to accelerate how they plan, build, and deliver software.About the RoleWe are seeking a technically deep, creativity-driven AI Deployment Engineer who is already a power user of AI coding tools and passionate about pushing the boundaries of developer productivity. You will partner directly with engineering leaders and hands-on builders to design, validate, and scale advanced AI workflows, often using Codex to prototype and build the very demos, integrations, and automations customers ultimately adopt.This is a highly cross-functional role that blends technical architecture, product strategy, and customer-facing leadership. You’ll work closely with Sales, Solutions Engineering, Product, Applied Engineering, and the broader Codex organization to advocate for customer needs, shape product direction, and accelerate the successful deployment of intelligent coding systems across some of the world’s most influential companies.This role is based in Seoul. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employeesIn this role, you will:Serve as the primary technical subject matter expert on OpenAI Codex for a portfolio of customers, embedding deeply with them to enable their engineering teams and build coding workflows.Partner directly with customers to design and implement AI-enhanced development workflows, from rapid prototyping through scalable production rollout.Build high-quality demos, reference implementations, and workflow automations, using Codex itself as part of your development process.Lead large-format workshops, technical deep dives, and hands-on enablement sessions that help engineering organizations adopt AI coding tools effectively and safely.Contribute technical content including examples, guides, patterns, and best practices to the OpenAI Cookbook to help the broader developer community accelerate their work with Codex.Gather high-fidelity product insights from real customer deployments and translate them into clear product proposals and model feedback for internal teams.Influence customer strategy and decision-making by framing how AI coding tools fit into their SDLC, technical roadmap, and organizational workflows.Serve as a trusted advisor on solution architecture, operational readiness, model configuration, security considerations, and best-practice adoption.You might thrive in this role if you:Have 8+ years of post-sales engineering or solutions architecture, working directly with customers.Have 2+ years of software engineering experience and a strong understanding of the software development life cycle.Are an active power user of AI coding tools and have deeply customized your own developer workflow; you have a point of view on what makes engineers more productive.Enjoy building scrappy, high-signal demos, integrations, and prototypes that clearly articulate what Codex can enable, often using Codex to accelerate your own development process.Have experience delivering large, high-impact workshops or technical training to engineering teams and know how to craft sessions that are engaging, hands-on, and outcomes-driven.Have contributed technical guides, patterns, or examples publicly and care about clarity, pedagogy, and community impact.Communicate complex technical concepts in clear, persuasive written and verbal form especially when helping customers make strategic decisions about where and how to apply AI.Are excited by ambiguous, rapidly evolving problem spaces and enjoy iterating toward novel solutions hand-in-hand with customers.Care about customer success, reliability, safety, and operational excellence as much as you care about technical ingenuity.About OpenAIOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.OpenAI Global Applicant Privacy PolicyAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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

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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.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.Today, LangChain, LangGraph, LangSmith, and Fleet 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.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.What 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 Bring5+ 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 Annual OTE range: $165,000–$280,000 USDCompensation Philosophy:We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. 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.BenefitsBenefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

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About Us Observe.AI is the AI Agents platform for customer experience, designed to help organizations deliver faster, smarter, and more efficient customer service at scale. The platform enables businesses to deploy specialized AI agents that autonomously execute work across the full CX lifecycle—from handling customer conversations to supporting frontline teams and optimizing operations. Each AI agent is purpose-built for a specific role, equipped to understand context, make decisions, take action, and continuously improve outcomes. This allows organizations to increase resolution speed, elevate service quality, and reduce operational costs while empowering your frontline team to focus on higher-value work. Built on a CX-native foundation, Observe.AI helps leading brands like DoorDash, Affordable Care, Signify Health, and Verida improve customer satisfaction, boost agent productivity, and deliver consistent, scalable performance across every customer interaction. Why Join Us We’re looking for an AI Agent Engineer to lead the charge in building and deploying enterprise-grade Voice, Chat AI agents and AI Copilot. This role is hands-on, customer-facing, and pivotal in bringing AI solutions to life - from design and integration to deployment and optimization. You’ll own the end-to-end lifecycle of AI agents: building, integrating, testing, demoing to clients, deploying into production, and tuning performance. What you’ll be doing Build & Deploy Agents: Own the implementation of AI agents including prompt design, workflow configuration, integrations, telephony setup, and evaluation frameworks. Client Engagement: Act as the primary technical partner for customers—lead regular demos, communicate progress, gather feedback, and guide solutions from concept to production. Systems Integration: Configure and connect systems using APIs—handling authentication, data mapping, error handling, and integrations with CRMs, knowledge bases, and other enterprise tools. Telephony Integration: Set up SIP/CCaaS/PSTN routing, pass metadata, configure fallbacks, and troubleshoot call quality. Prompt Design & Optimization: Write and refine prompts for LLM-driven agents, monitor performance, test iteratively, and ensure agents meet automation and containment targets. Strategic Partner: Translate customer requirements into actionable solutions; work consultatively to unblock challenges in security, connectivity, or knowledge ingestion. Cross Functional Collaboration: Collaborate with product/engineering teams to escalate platform gaps and resolve deep technical fixes and platformization, while independently driving leading client implementations. What you’ll Bring Bachelor’s degree in Computer Science, Engineering, or a related technical field 3+ years in conversational AI, solution engineering, system integration, or delivering AI/LLM-based applications in customer environments, software engineering, or system integration with hands-on delivery of AI/LLM-based solutions. Strong ability to communicate and  lead customer-facing discussions - from deep technical troubleshooting to weekly project demos. Ability to explain complex technical concepts to non-technical audiences.  Must have strong hands-on skills in prompt design, workflow building and API integration (SIP, Twilio, Amazon Connect, etc.). Familiarity with LLMs (GPT, Claude, Gemini), vector DBs, and orchestration frameworks (LangChain, LlamaIndex, etc.). Working knowledge of retrieval-augmented generation (RAG) concepts, implementation patterns and performance optimization. Programming experience in Python, JavaScript, or similar for scripting and integrations Strong problem-solving mindset: ability to find workarounds, unblock integrations, and adapt to customer-specific ecosystems.  Experience with integration tools and Integration Platform-as-a-Service (iPaaS) providers, such as n8n, Zapier, or similar platforms and proficiency in API integrations and data flow management is a plus. Familiarity with telephony or voice systems (SIP, CCaaS, PSTN) is a plus.  Why You’ll Love It Here   Competitive compensation including equity: Market-aligned base pay, performance incentives, and meaningful equity ownership Excellent medical, dental, and vision insurance options: Comprehensive medical, dental and vision benefits for employees and eligible dependents Flexible Paid Time Off: Our unlimited, flexible PTO policy empowers you to take the time you need to recharge, maintain balance, and perform at your best. Additional Time to Recharge: 10 company holidays, an annual company-wide Winter Break, and paid parental leave to fully support life outside of work. 401(k) plan: Long-term financial planning support with tax-advantaged retirement savings Quarterly Lifestyle Spending Account: Flexible quarterly stipend to support wellness, learning and professional development, and personal growth Monthly Mobile + Internet Stipend: Support for remote and hybrid work connectivity needs Pre-tax Commuter Benefits: Tax-efficient transit and commuting support for hybrid and in-office employees Autonomy and Agency: Play a meaningful role in scaling a category-defining GenAI platform transforming the future of customer experience. Salary Range The base salary compensation range targeted for this full-time position is $108 - 170K per annum. Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives and equity (in the form of options). This salary range is an estimate, and the actual salary may vary based on the Company’s compensation practices. Our Commitment to Inclusion and Belonging Observe.AI is an Equal Employment Opportunity employer that proudly pursues and hires a diverse workforce. Observe AI does not make hiring or employment decisions on the basis of race, color, religion or religious belief, ethnic or national origin, nationality, sex, gender, gender identity, sexual orientation, disability, age, military or veteran status, or any other basis protected by applicable local, state, or federal laws or prohibited by Company policy. Observe.AI also strives for a healthy and safe workplace and strictly prohibits harassment of any kind. We welcome all people. We celebrate diversity of all kinds and are committed to creating an inclusive culture built on a foundation of respect for all individuals. We seek to hire, develop, and retain talented people from all backgrounds. Individuals from non-traditional backgrounds, historically marginalized or underrepresented groups are strongly encouraged to apply. If you are ambitious, make an impact wherever you go, and you're ready to shape the future of Observe.AI, we encourage you to apply. For more information, visit www.observe.ai.  #LI-Hybrid

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About DecagonDecagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences.Our technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel.We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others.We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team.About the TeamOver the past few years, development of LLMs has evolved at a rapid pace. It’s not enough for our customers to just “set it and forget it” when it comes to AI software. Truly successful AI Agents require guidance and input throughout the development lifecycle.The Agent Product Management team drives this journey as Decagon’s in-house experts on building, deploying, and scaling AI agents. Agent PMs work directly with customers to bring their AI agents to life, and then grow each Agent into a core part of each company’s businesses. As one of our early APM’s, you will deploy our technology into some of the world’s most influential businesses, driving real world business impact as one part Product Manager, one part AI expert.About the RoleOn the APM team you’ll own each stage of the AI Agent building process. This can include:Collaborating with engineering to design a new product featureWriting and testing prompt logic for a specific customer use caseWorking with a customer’s executive team to define their AI roadmapYou’ll partner closely with every team at Decagon: Go-To-Market, Design, Engineering, and across our leadership team. You’ll become a key source of customer insight guiding our long-term product roadmap.APMs at Decagon own their own portfolio of agents from end-to-end and are trusted to make real impact. This role is for someone who dives deep into complex business problems, builds elegant solutions and then scales them out to millions users.In this role, you willBuild, Design and optimize Enterprise-quality AI agents in collaboration with customers — understanding their workflows, pain points, and goals.Embed deeply within strategic customers to understand their business challenges and serve as a strategic advisor to their AI roadmapRun tight feedback loops into Engineering — influence feature development based on real customer needs.Represent Decagon externally — working closely with customers and prospects, participating in key deployments.Your background looks something like thisHave 6+ years of relevant experience (e.g., product manager, engagement manager, consultant, founder, etc.)Fluent in German with professional experience working and communicating in German-speaking environments. Deep technical acumen — able to understand and shape AI agent designs.Strong communication and relationship-building skills.Comfort working in fast-moving, ambiguous environments where you shape solutions as much as you implement them.Even better if you haveA Computer Science, Engineering, or Math degree — or equivalent technical experience.Compensation£145k – £200K + Offers EquityBenefitsWe proudly offer the following benefits for our full-time employees:Take what you need vacation policy (subject to local requirements; UK employees receive 25 days of statutory leave)Medical, Dental, and Vision benefits for you and your familyLife Insurance and Disability BenefitsRetirement Plan (e.g., 401K, pension)Parental LeaveFertility and family building benefits through CarrotDaily lunches and snacks in the office to keep you at your bestThese benefits are described in more detail in Decagon’s policies, may vary by location, and can change at any time according to applicable compensation and benefits plans.

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