Simulation And Modeling Lead in San Francisco

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role You will build the low-level device runtime that turns compiled programs into efficient, functional and performant execution on OpenAI’s custom AI accelerator. This software will schedule kernel launches, manage device memory and address spaces, coordinate synchronization, and expose reliable abstractions to higher-level runtimes and frameworks. You will work at the boundary of software and hardware, partnering with compiler, kernel, architecture, verification, and silicon teams to define interfaces and validate behavior. You will also use and improve event-based, cycle-accurate simulation to develop runtime capabilities before silicon is available, diagnose performance and correctness issues, and guide hardware-software co-design. In this role, you will: Design and implement the low-level device runtime for OpenAI custom silicon. Build kernel-launch scheduling, command submission, queueing, dependency tracking, and completion handling. Manage device memory spaces, allocation, virtual-to-physical mappings, data movement, and lifetime across concurrent workloads. Implement synchronization primitives, events, barriers, streams, and ordering guarantees that are correct and efficient. Define clean interfaces between the runtime, drivers, firmware, compiler-generated code, kernels, and higher-level execution systems. Use event-based, cycle-accurate simulators to develop, validate, debug, and performance-tune runtime behavior before and after silicon availability. Di

About the Team Our Robotics team is focused on unlocking general-purpose robotics and pushing towards AGI-level intelligence in dynamic, real-world settings. Working across the entire model stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors. We strive to seamlessly blend high-level AI capabilities with the constraints of physical systems to improve peoples’ lives. About the Role We are seeking a senior Actuator Electromagnetic Design Engineer to lead the development of custom electromechanical actuators for advanced robotic systems. You will own actuator development from early architecture and concept generation through prototype validation and system integration, partnering closely with mechanical, electrical, controls, firmware, reliability, and manufacturing teams. This role focuses on the design, integration, and validation of precision electromechanical systems, including motors, transmissions, sensing, structural components, and thermal architectures. You will help drive actuator development across the full engineering lifecycle while establishing scalable design, test, and integration practices for future robotic platforms. This role is based in San Francisco, CA, and requires in-person presence 4 days a week. In this role, you will: Lead the architecture, design, and integration of custom robotic actuators, including the design, simulation, integration and sourcing of custom electromagnetic components. Define actuator requirements and system-level trade studies around torque density, bandwidth, efficiency, thermal performance, inertia, reliability, manufacturability, and cost. Design precision electromechanical assemblies with strong attention to tolerances, alignment, load paths, thermal expansion, sealing, wear, and serviceability. Drive actuator integration into robotic systems, partnering closely with controls, firmware, electrical, and robotics software teams to optimize closed-loop performance. Devel

What you’ll do Be the generalist EE for the scanner system: integration, bring-up, debugging, and making the electrical side of the device reliable and serviceable. Own ultrasound experimentations that feeds the image reconstruction team Design and execute experiment setups for transducer characterization (element sensitivity, bandwidth, cross-talk mapping, beam profile measurements) and ex vivo / phantom clinical testing. Acquire, process, and analyze RF and baseband signals for data quality assessment and benchmarking. Design simple boards and adapters as needed (monitoring, power/safety, interface/conditioning), and take them from prototype through a stable revision. Prototype quickly, then harden what works: wiring/harnessing, grounding, safety interlocks, and reliable integration across subsystems. Own practical test setups and documentation (fixtures, scripts, procedures) that make experiments repeatable and results comparable over time. What we’re looking for Strong hands-on EE background with experience building, debugging, and iterating on real systems in the lab. Solid understanding of signal processing fundamentals — knows what to measure, how to condition and digitize it, and how to evaluate signal quality in the context of an imaging system (SNR, bandwidth, dynamic range, artifacts). Comfortable spanning system integration + occasional design work (schematics/layout reviews or light PCB design) in a fast-moving environment. Ability to work at the boundary between hardware and algorithms: measure reality, communicate constraints, and help close gaps vs simulation. High agency and practicality: able to set up experiments, get trustworthy data, and unblock others on a lean team. Useful experience Analog/mixed-signal, or high-speed data capture experience; strong instincts for instrumentation and noise/debugging. Ultrasound or acoustic sensor handling: hydrophone calibration and field mapping, transducer impedance characterization, element-level sensitivity

About the Team The Workload Networking team is responsible for the collective communication stack used in our largest training jobs. Using a combination of C++ and CUDA we work on novel collective communication techniques that enable efficient training of our flagship models on our largest custom built supercomputers. The models we train are key ingredients to the AI research progress at OpenAI and the field as a whole, and we continually incorporate learnings from our entire research org into our training platform. About the Role As a Software Engineer, Networking you will design and implement custom networking collectives that are tightly integrated into our training stack. We’re looking for people who have a background in low level performance critical software. Experience with collective communication is a bonus. 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: Collaborate closely with ML researchers to design and implement efficient collective operations in C++ and CUDA. Ensure that our largest training jobs take full advantage of the different network transports used in our supercomputers. Work on simulations to inform our future supercomputer network designs. You might thrive in this role if you: Have written distributed algorithms using RDMA in the past. Are comfortable writing low level performance sensitive CPU and/or GPU code. Are familiar with network simulation techniques. About OpenAI OpenAI 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, voic

About the Team The Enablement team translates OpenAI’s product innovation into real-world customer impact by equipping customer-facing teams with the knowledge, practice, and frameworks they need to succeed. Within GTM onboarding, we establish a shared foundation during the first 30 days and build deeper role readiness for technical GTM teams as they progress through ramp. About the Role OpenAI is hiring a GTM Technical Onboarding Program Manager to define and deliver the role-specific onboarding experience for technical customer-facing GTM roles. Foundational onboarding establishes a common baseline during the first 30 days. This role owns the deeper development that follows, with a particular focus on days 30–90, when new hires need to translate product and deployment knowledge into practical, job-specific capability. You will partner with technical GTM leaders, Product, and subject-matter experts to turn complex product and deployment concepts into role-specific curricula, hands-on practice, assessments, certifications, and manager reinforcement. Success means technical GTM new hires build the product fluency, scoping ability, solution judgment, and customer-facing confidence required for their roles. Managers have clear readiness signals, learning experiences stay current as products evolve, and role-specific ramp becomes repeatable across teams and regions. In this role, you will: Own the design and delivery of day 30–90 role-specific onboarding for technical GTM roles Define learning outcomes and readiness standards in partnership with technical GTM leaders Build curricula and learning paths that translate complex product and deployment concepts into job-specific behavior Design and facilitate hands-on experiences such as labs, demos, simulations, technical discovery practice, and customer scenarios Create assessments, certifications, and manager-ready signals of proficiency and deployment readiness Partner with Product, technical subject-matter experts, and G

About the Team Codex is OpenAI’s first-party developer product focused on agentic software engineering. We’re building tools that help engineers design, write, test, and ship code faster—safely and at scale. We partner tightly with research and product to translate model advances into tangible developer productivity. About the Role As a Data Scientist on Codex, you will measure and accelerate product-market fit for AI developer tools. You’ll define what “developer productivity” means for our product, run experiments on new coding models and UX, and pinpoint where the model helps or hurts across languages and tasks. Your insights will directly shape how an entire industry builds software. 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 Embed with the Codex product team to discover opportunities that improve developer outcomes and growth Design and interpret A/B tests and staged rollouts of new coding models and product features Define and operationalize metrics such as suggestion acceptance, edit distance, compile/test pass rates, task completion, latency, and session productivity Build dashboards and analyses that help the team self-serve answers to product questions (by language, framework, repo size, task type) Diagnose failure modes and partner with Research on targeted improvements (model quality signals, user feedback, evals) You might thrive in this role if you have 5+ years in a quantitative role at a developer-facing or high-growth product Fluency in SQL and Python; comfort with experiment design and causal inference Experience defining product metrics tied to user value Ability to communicate clearly with PM, Eng, and Design—and to influence product direction You could be an especially great fit if you have Strong programming background; ability to prototype, run simulations, and reason about code quality Familiarity with IDE/extensi

About the Team OpenAI’s mission is to ensure that general-purpose artificial intelligence benefits all of humanity. The Design Systems team creates the foundations that help teams across OpenAI build coherent, high-quality experiences at scale. Accessibility is fundamental to that work. We’re building the shared standards, components, tools, and practices that make inclusive experiences the default across OpenAI’s products and platforms. About the Role In this role, you’ll lead OpenAI’s company-wide accessibility program from within Design Foundations. You’ll pair strategy and organizational influence with hands-on product design—advocating for disabled people, removing barriers across complete customer journeys, and establishing durable ownership throughout the company. This is an opportunity to define accessibility for a new generation of products spanning web, mobile, desktop, voice, AI, and hardware. You’ll help teams consider the many ways people perceive, understand, navigate, and interact with technology, going beyond minimum compliance to create experiences that are genuinely useful and inclusive. Working across design, engineering, research, product, go-to-market, and legal, you’ll make accessibility an expected part of product quality—not a final review or the responsibility of a single expert. This role is based in our San Francisco HQ. We offer relocation assistance to new employees. In this role you will: Define OpenAI’s accessibility strategy, roadmap, governance, priorities, and measures of progress. Design and ship accessible experiences while identifying systemic barriers across complete customer journeys. Build accessibility into our design system through inclusive components, tokens, interaction patterns, Figma libraries, documentation, and engineering guardrails. Center disabled people through participatory research, usability studies, and assistive-technology testing rather than relying solely on assumptions, simulations, or automated tools. Des

About the Team OpenAI’s Hardware organization develops silicon and system-level solutions designed for the unique demands of advanced AI workloads. The team is responsible for building the next generation of AI-native silicon while working closely with software and research partners to co-design hardware tightly integrated with AI models. In addition to delivering production-grade silicon for OpenAI’s supercomputing infrastructure, the team also creates custom design tools and methodologies that accelerate innovation and enable hardware optimized specifically for AI. About the Role As an Engineer on our hardware optimization and co-design team, you will co-design future hardware from different vendors for programmability and performance. You will work with our kernel, compiler and machine learning engineers to understand their unique needs related to ML techniques, algorithms, numerical approximations, programming expressivity, and compiler optimizations. You will evangelize these constraints with various vendors to develop and influence future hardware architectures towards efficient training and inference on our models. If you are excited about efficiently distributing a large language model across devices, dealing with and optimizing system-wide/rack-wide networking bottlenecks and eventually tailoring the compute pipe and memory hierarchy of the hardware platform, simulating workloads at different abstractions and working closely with our partners, this is the perfect opportunity! 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. Key Responsibilities Co-design future hardware for programmability and performance with our hardware vendors Assist hardware vendors in developing optimal kernels and add support for it in our compiler Develop performance estimates for critical kernels for different hardware configurations and drive decisions on compute core and memory h

About the Team OpenAI’s People team is committed to hiring, engaging, and supporting world-class talent to help safely build and deploy universally beneficial Artificial General Intelligence (AGI). The Global Employee Relations and People Standards team brings together expertise in employee relations, employment investigations, and People compliance, policy, and standards. We play a critical role in shaping how OpenAI supports its people through complexity, growth, and change. Our team guides and supports the company through some of its most nuanced and high-impact people challenges. We operate with deep context and care, balancing trust, judgment, and creativity in every situation. We don’t default to predefined frameworks. Instead, we take a principled yet flexible approach, designing thoughtful, tailored solutions that reflect our values, the needs of our employees, and the unique pace of OpenAI. 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. About the Role We’re looking for a Senior Employee Relations Partner to focus on the non-investigative side of ER work, supporting high-trust, high-impact people matters. This includes conflict resolution, high-risk performance management, sensitive employee exits, and navigating workplace dynamics that require thoughtful, strategic support even when they don’t involve formal investigations. This role will report to the senior manager of the team. We're looking for someone who brings creativity, flexibility, and a deeply human-centered approach to solving people challenges. You’re energized by complexity and nuance, and instinctively seek out tailored, thoughtful solutions rather than one-size-fits-all answers. You don’t just apply rules; you understand context, think strategically, and help leaders make principled decisions that reflect our values and evolving culture. This role is a fit for someone who adapts quickly, th