Frontier Ux Engineer Jobs

About the Team OpenAI’s Physical Engineering work explores how frontier AI can help people design, simulate, and build better physical products. We work directly with customers to identify high-value engineering applications that shorten development cycles, improve product performance, and create measurable business value. About the Role We are hiring a Physical Engineering Business Lead to bring firsthand product engineering experience into our customer work. You’ll combine deep familiarity with CAD, simulation, or related engineering tools with the ability to lead customer discovery, explain complex ideas clearly, and turn promising use cases into high-impact projects. This is a hands-on, customer-facing role. You’ll work closely with customer engineering teams, senior leaders, forward-deployed engineers (FDEs), and account teams from early discovery through delivery. You’ll help frame valuable design and simulation problems, guide projects with practical engineering judgment, and support adoption and measurable outcomes. You’ll also turn what we learn from customers into product feedback, reusable delivery methods, and recommendations for our go-to-market and partnership strategies. As the work grows, this role may evolve into broader practice leadership. Key Responsibilities Lead discovery and workshops with customer engineering teams and senior leaders to identify high-value design and simulation use cases Develop promising use cases into significant projects with FDE and account teams, forming clear hypotheses about value, feasibility, engineering constraints, and adoption Work alongside FDEs and customer teams through delivery, bringing practical engineering context, surfacing risks early, and helping projects achieve measurable outcomes Explain how AI can improve physical-product engineering, grounded in real experience with CAD, simulation, engineering workflows, and design tradeoffs Build customer confidence through clear technical storytelling, compelling

About the team The OpenAI for Government team brings frontier AI to public institutions to help them achieve their missions. We partner with government leaders, mission owners, and technical teams to deploy AI tools responsibly, with the reliability, security, and support needed for meaningful use. Our Federal Civilian and State & Local Government business supports public institutions across a broad range of missions. We help these customers apply frontier AI to public services, knowledge work, research, and mission operations through hands-on delivery, tailored enablement, and collaboration with their teams. About the Role The Strategic Delivery Lead (SDL), Federal Civilian & State and Local Government, will shape and deliver high-impact AI engagements across federal civilian agencies and state and local governments. You will turn customer priorities into practical deployments and sustained use, helping government leaders and mission teams apply OpenAI technology to public services, knowledge discovery, and operational workflows. This individual contributor role reports to the leader of Federal Civilian and State & Local Government. You will work alongside Account Directors and Applied AI Architects across assigned engagements, coordinating Research, Product, Engineering, Policy, Security, and Enablement resources. Account Directors own commercial strategy, contracts, and quota; you own delivery coordination, adoption, and customer outcomes, without an individual sales quota. You will lead execution across customer and OpenAI workstreams: define scope, milestones, acceptance criteria, dependencies, and success measures; surface risks; resolve blockers; and communicate progress to agency executives, program leaders, and working teams. You are accountable for agreed delivery commitments and customer acceptance. Engineering and Product teams remain responsible for technical implementation and operation of the systems they own. This is a high-trust, high-au

Biohub is the first large-scale initiative bringing frontier AI models, massive compute, and frontier experimental capabilities under one roof. We're building a general-purpose system to accelerate scientific discovery, integrating frontier AI models, biological foundation models, and lab capabilities, with the ultimate goal of curing disease. Our technology powers scientists around the world, translating AI capabilities into tools that accelerate research everywhere. The Team Our decoding inflammation team builds tools to enable precise molecular-level measurements of inflammation within human tissues in real time, and develop proactive, early interventions that can be deployed when inflammation — which underlies the most significant causes of death worldwide — first flares in the body. You can learn more about our work here . Our team collaborates with three powerhouse universities - Northwestern University, the University of Chicago, and the University of Illinois Urbana-Champaign - to develop first-in-class technologies and make breakthroughs. Our Vision Pursue large scientific challenges that cannot be pursued in conventional environments Enable individual investigators to pursue their riskiest and most innovative ideas Facilitate research by scientists and clinicians at our home institutions and beyond We are a team of passionate individuals powered by technology, guided by scientific research, and driven by collaboration, working toward a mission to cure or prevent all disease. The Opportunity To support our AI models and applications in inflammation and immunology, Biohub Chicago is building a lab that runs biology experiments at a scale and consistency that manual work can't reach. We are seeking a Research Associate experienced in hands-on cell biology to work closely with automation engineers and scientists, performing consistent cell maintenance, executing experiments on and off automated systems, and developing the QC metrics which will form

Biohub is the first large-scale initiative bringing frontier AI models, massive compute, and frontier experimental capabilities under one roof. We're building a general-purpose system to accelerate scientific discovery, integrating frontier AI models, biological foundation models, and lab capabilities, with the ultimate goal of curing disease. Our technology powers scientists around the world, translating AI capabilities into tools that accelerate research everywhere. The Team Our immune cell reprogramming team integrates foundational research on immunology and disease biology with AI-modeling to develop engineered cells that harness our own immune system to detect and treat early signs of age-related diseases, like cancer, Alzheimer’s, and Parkinson’s. These technologies will enable precise, context-dependent therapeutic responses only when and where it is needed. You can learn more about our work here . Our work brings together three powerhouse universities - Columbia University, The Rockefeller University, and Yale University - into a single collaborative technology and discovery engine. Our Vision Pursue large scientific challenges that cannot be pursued in conventional environments Enable individual investigators to pursue their riskiest and most innovative ideas Facilitate research by scientists and clinicians at our home institutions and beyond We are a team of passionate individuals powered by technology, guided by scientific research, and driven by collaboration, working toward a mission to cure or prevent all disease. The Opportunity The Advanced Single Cell Technologies group provides critical single cell profiling and perturbation assays, technology, and expertise to the Biohub NY community. The goal of the platform is to develop cutting-edge single-cell technologies in collaborations related to studying human disease and the interaction of immune cells with human organs. More information can be found on the lab website ( https://biohub.org/single-

About the team The Applied AI Engineering team works closely with frontier startups. We are trusted advisors to, and thought partners with, startups to ensure that OpenAI’s technology is deployed safely and effectively, whilst also partnering with engineering, research, and product to turn those insights into evaluation systems, product improvements, and better model behavior. This team sits at the intersection of customer reality and model quality. We combine hands-on technical depth with strong product judgment, helping translate complex, high-value use cases into clear signals that can improve both the customer experience and the underlying systems. About the Role As an Applied AI Engineer focused on Codex for startups, you will help developers and founders transform how they build and ship software. You’ll combine hands-on engineering, startup experience, and compelling technical communication to help teams turn the potential of AI coding tools into practical, effective workflows. Presentations and community engagement are central to this role. You will engage developers and founders through technical talks, live demos, workshops, and programmes across the startup ecosystem, alongside targeted work with individual customers. You’ll build reusable tools and resources that extend your impact, and bring insights from developers back to OpenAI’s Product, Research, and Engineering teams. This role is well suited to someone who enjoys both hands-on building and sharing what they learn with others. You should be as excited to lead a room of developers, deliver an engaging presentation, and build relationships across the startup community as you are to explore a technical problem in code—with a focus on sustained adoption and meaningful improvements in how startups work. In this role, you will: Partner with top startups to identify where Codex can have the greatest impact on how their teams build and ship software. Design and lead technical talks, live demos, workshops,

About the team The Applied AI Engineering team works closely with frontier startups. We are trusted advisors to, and thought partners with, startups to ensure that OpenAI’s technology is deployed safely and effectively, whilst also partnering with engineering, research, and product to turn those insights into evaluation systems, product improvements, and better model behavior. This team sits at the intersection of customer reality and model quality. We combine hands-on technical depth with strong product judgment, helping translate complex, high-value use cases into clear signals that can improve both the customer experience and the underlying systems. About the Role As an Applied AI Engineer focused on Codex for startups, you will help developers and founders transform how they build and ship software. You’ll combine hands-on engineering, startup experience, and compelling technical communication to help teams turn the potential of AI coding tools into practical, effective workflows. Presentations and community engagement are central to this role. You will engage developers and founders through technical talks, live demos, workshops, and programmes across the startup ecosystem, alongside targeted work with individual customers. You’ll build reusable tools and resources that extend your impact, and bring insights from developers back to OpenAI’s Product, Research, and Engineering teams. This role is well suited to someone who enjoys both hands-on building and sharing what they learn with others. You should be as excited to lead a room of developers, deliver an engaging presentation, and build relationships across the startup community as you are to explore a technical problem in code—with a focus on sustained adoption and meaningful improvements in how startups work. In this role, you will: Partner with top startups to identify where Codex can have the greatest impact on how their teams build and ship software. Design and lead technical talks, live demos, workshops,

About the team The Applied AI Engineering team works closely with frontier startups. We are trusted advisors to, and thought partners with, startups to ensure that OpenAI’s technology is deployed safely and effectively, whilst also partnering with engineering, research, and product to turn those insights into evaluation systems, product improvements, and better model behavior. This team sits at the intersection of customer reality and model quality. We combine hands-on technical depth with strong product judgment, helping translate complex, high-value use cases into clear signals that can improve both the customer experience and the underlying systems. About the Role As an Applied AI Engineer focused on Codex for startups, you will help developers and founders transform how they build and ship software. You’ll combine hands-on engineering, startup experience, and compelling technical communication to help teams turn the potential of AI coding tools into practical, effective workflows. Presentations and community engagement are central to this role. You will engage developers and founders through technical talks, live demos, workshops, and programmes across the startup ecosystem, alongside targeted work with individual customers. You’ll build reusable tools and resources that extend your impact, and bring insights from developers back to OpenAI’s Product, Research, and Engineering teams. This role is well suited to someone who enjoys both hands-on building and sharing what they learn with others. You should be as excited to lead a room of developers, deliver an engaging presentation, and build relationships across the startup community as you are to explore a technical problem in code—with a focus on sustained adoption and meaningful improvements in how startups work. In this role, you will: Partner with top startups to identify where Codex can have the greatest impact on how their teams build and ship software. Design and lead technical talks, live demos, workshops,

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g., Seaborn , Luigi ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: Modal's LLM inference platform delivers frontier performance for open-source models with best-in-class elasticity and developer experience, made in part possible by our custom runtime with GPU memory snapshots and multi-cloud substrate . We're looking for a leader to own the direction and execution of this platform to continue to establish us as the clear market leader, working closely with customers like Cognition, Doordash, Ramp, and many more. You'll be leading a group of highly talented engineers working on our market-leading LLM inference offering, spanning the serving stack, routing infrastructure, internal agentic optimization platform, and the user-facing product surface area. This is a hands-on leadership role — expect to split your time between technical contribution, product shaping and people management depending on what the team needs. You'll set direction, remove blockers, and build

About the Team API Frontiers turns OpenAI’s frontier models into production APIs that developers can use to build reliable products and agents. We own the core path connecting models to developers through the Responses API, with a focus on safety, reliability, and speed. Working closely with Research, Safety, Codex, and other API teams, we bring new model capabilities into production and improve them through developer feedback. About the Role We are looking for a backend software engineer to build and operate the services behind the Responses API. You will shape API behavior, bring new capabilities from research into production, and make long-running agent workflows dependable and fast. The work combines distributed systems engineering with product judgment: designing useful developer interfaces, managing staged rollouts, and following production issues through to durable fixes. In this role, you will: Design, build, and operate APIs and backend services that bring frontier model capabilities to developers. Partner with Research, Safety, Codex, and API teams to define API behavior and deliver safe, staged launches. Build API capabilities for agent workflows, including task delegation, context sharing, and parallel execution. Strengthen long-running request reliability across timeouts, cancellation, streaming, and background execution. Improve request-processing performance and tail latency through profiling, efficient systems code, and persistent connections. Turn developer feedback and production failures into better observability, diagnostics, and lasting product improvements. Your background might look something like: 5+ years of experience building and operating backend services or developer-facing APIs in production. Strong software engineering fundamentals, with practical knowledge of distributed systems, concurrency, and asynchronous execution. Ability to diagnose production failures and performance bottlenecks using observability data and profiling. Product

Biohub is the first large-scale initiative bringing frontier AI models, massive compute, and frontier experimental capabilities under one roof. We're building a general-purpose system to accelerate scientific discovery, integrating frontier AI models, biological foundation models, and lab capabilities, with the ultimate goal of curing disease. Our technology powers scientists around the world, translating AI capabilities into tools that accelerate research everywhere. The Team The Chan Zuckerberg Biohub New York is an independent nonprofit research institute that brings together three powerhouse universities - Columbia University, The Rockefeller University, and Yale University - into a single collaborative technology and discovery engine. Biohub itself supports some of the brightest, boldest engineers, data scientists, and biomedical researchers to investigate the fundamental mechanisms underlying disease and develop new technologies that will lead to actionable diagnostics and effective therapies. We are guided by our values of scholarly excellence; disruptive innovation; hands-on engineering/hacking/building; partnership and collaboration; open communication and respect; inclusiveness; and opportunity for all. Our Vision We pursue large scientific challenges that cannot be pursued in conventional environments We enable individual investigators to pursue their riskiest and most innovative ideas The technologies developed at Biohub facilitate research by scientists and clinicians at our home institutions and beyond Diversity of thought, ideas, and persp

Biohub is the first large-scale initiative bringing frontier AI models, massive compute, and frontier experimental capabilities under one roof. We're building a general-purpose system to accelerate scientific discovery, integrating frontier AI models, biological foundation models, and lab capabilities, with the ultimate goal of curing disease. Our technology powers scientists around the world, translating AI capabilities into tools that accelerate research everywhere. The Team Our immune cell reprogramming team integrates foundational research on immunology and disease biology with AI-modeling to develop engineered cells that harness our own immune system to detect and treat early signs of age-related diseases, like cancer, Alzheimer’s, and Parkinson’s. These technologies will enable precise, context-dependent therapeutic responses only when and where it is needed. You can learn more about our work here . Our work brings together three powerhouse universities - Columbia University, The Rockefeller University, and Yale University - into a single collaborative technology and discovery engine. Our Vision Pursue large scientific challenges that cannot be pursued in conventional environments Enable individual investigators to pursue their riskiest and most innovative ideas Facilitate research by scientists and clinicians at our home institutions and beyond We are a team of passionate individuals powered by technology, guided by scientific research, and driven by collaboration, working toward a mission to cure or prevent all disease. The Opportunity Biohub NY is seeking an accomplished computational biologist experienced in machine learning and transcriptomic data analyses to join our interdisciplinary team. Within the Biohub NY “Immune Cell Re-Programming” group, this role requires experience in research settings, a background in biology, and a proven ability to design, evaluate, and publish innovative computational methodologies that leverage machine learnin

About the Team The Industry Marketing team helps OpenAI bring frontier AI to the industries where it can create meaningful, measurable impact. We work across Product, GTM, Communications, Partnerships, Policy, Security, and Research to translate model and product capabilities into industry narratives, field motions, customer proof, and launch programs that help enterprises adopt AI responsibly. About the Role As Product Marketing Manager, Cybersecurity, you will help define how OpenAI brings frontier AI to cyber defenders. This role sits at the center of Daybreak, OpenAI’s cybersecurity initiative to help defenders see risk earlier, act sooner, and build software that is resilient by design. You will shape the market narrative, build the field-facing operating system, and coordinate cross-functional execution across product launches, customer proof, partner moments, events, and account-based campaigns. You will help senior security leaders understand how OpenAI models, Trusted Access for Cyber, Codex Security, and related workflows can support real defensive work. We’re looking for a product marketer who combines strategic narrative, technical curiosity, enterprise go-to-market judgment, and program leadership. The right person can turn fast-moving capabilities into clear positioning, credible assets, and practical field execution. In this role, you will: Own positioning and messaging for OpenAI’s cybersecurity offering, including Daybreak, Trusted Access for Cyber, Codex Security, and related product surfaces. Build field-ready assets for account directors, solutions engineers, security leaders, and executive audiences, including first-call decks, one-pagers, use-case libraries, customer stories, and proof-point packages. Translate frontier model capabilities into simple, accurate, and defensible go-to-market language for senior enterprise buyers and security practitioners. Partner with Product, Research, Security, Policy, Communications, Partnerships, and GTM to c

About BlockTech BlockTech is an algorithmic trading firm operating at the frontier of global crypto derivatives and spot markets. We trade 24/7 across some of the fastest-moving, most data-rich venues in finance. Crypto remains one of the few markets where a researcher can still meaningfully move the edge: abundant data, novel microstructure, and the shortest possible loop between a research idea and live PnL. We're looking for an experienced Quantitative Researcher to take ownership of that edge and push it further. The role This is a senior, hands-on research seat on our trading floor. You'll own a research agenda end-to-end from hypothesis, dataset construction, feature engineering, model training, backtesting, live deployment, monitoring, and iteration. You'll be trusted to set its direction. You'll work shoulder-to-shoulder with fellow researchers, traders and analysts, shape how we price and trade, and help raise the bar for research across the floor, including mentoring less experienced researchers and influencing the tools and standards the team relies on. You will: Own price-prediction, signal, execution, and anomaly-detection models across crypto derivatives and spot markets from idea to live PnL using state-of-the-art ML Shape our research, backtesting, and trading infrastructure together with engineers, so good ideas reach production quickly and safely Own models in production: monitor live performance, diagnose decay, and iterate on what you ship Set research direction alongside traders, deciding which trades are worth making and why Raise the research bar by mentoring colleagues, reviewing work, and setting standards for rigour What we're looking for 4+ years of hands-on quantitative research and/or applied ML experience, with a track record of models you've taken into production trading live A strong academic foundation in a quantitative discipline (mathematics, physics, statistics, computer science, ML/AI, or similar) Fluency in Python and the modern

About BlockTech BlockTech is an algorithmic trading firm operating at the frontier of global crypto derivatives and spot markets. We trade 24/7 across some of the fastest-moving, most data-rich venues in finance. Crypto is one of the few markets where the gap between a good model and live PnL comes down to how fast and how reliably you can ship it. Abundant data, novel microstructure, and a short path to production mean the quality of our infrastructure directly moves the edge. We're looking for a Quantitative Developer to build that infrastructure and get our models into production. The role This is a hands-on engineering seat on our trading floor. You'll own the infrastructure that turns research models into production trading systems, working primarily in Python and Rust, the language our models and systems are written in. You'll build the frameworks and tooling that let quants ship their code to production and keep those systems running once they're live. You'll work shoulder-to-shoulder with researchers, traders, and fellow engineers, building the tooling, pipelines, and standards that let good ideas reach production quickly and safely, and helping raise the engineering bar across the floor. You will Build and own the infrastructure that takes models from research to production - data pipelines, backtesting, deployment, and monitoring. Turn research prototypes into robust, performant, production-grade code that runs reliably in live trading Work closely with quantitative researchers and traders to get new models live quickly and safely Own the systems you ship in production: monitor performance, diagnose issues, and keep latency and reliability high Improve the tools, standards, and pipelines the team relies on, raising the engineering bar across the floor What we're looking for 2+ years of software engineering experience, with a track record of shipping production-grade systems A strong academic foundation in a STEM discipline (computer science, mathematics, p

About BlockTech BlockTech is an algorithmic trading firm operating at the frontier of global crypto derivatives and spot markets. We trade 24/7 across some of the fastest-moving, most data-rich venues in finance. Crypto remains one of the few markets where a researcher can still meaningfully move the edge: abundant data, novel microstructure, and the shortest possible loop between a research idea and live PnL. We're looking for an experienced Quantitative Researcher to take ownership of that edge and push it further. The role This is a senior, hands-on research seat on our trading floor. You'll own a research agenda end-to-end from hypothesis, dataset construction, feature engineering, model training, backtesting, live deployment, monitoring, and iteration. You'll be trusted to set its direction. You'll work shoulder-to-shoulder with fellow researchers, traders and analysts, shape how we price and trade, and help raise the bar for research across the floor, including mentoring less experienced researchers and influencing the tools and standards the team relies on. What you'll do Own price-prediction, signal, execution, and anomaly-detection models across crypto derivatives and spot markets from idea to live PnL using state-of-the-art ML Shape our research, backtesting, and trading infrastructure together with engineers, so good ideas reach production quickly and safely Own models in production: monitor live performance, diagnose decay, and iterate on what you ship Set research direction alongside traders, deciding which trades are worth making and why Raise the research bar by mentoring colleagues, reviewing work, and setting standards for rigour What we're looking for 4+ years of hands-on quantitative research and/or applied ML experience, with a track record of models you've taken into production trading live A strong academic foundation in a quantitative discipline (mathematics, physics, statistics, computer science, ML/AI, or similar) Fluency in Python and the m