Model Designer in San Francisco

AI Systems Engineer - Codex Core Agents About The Team The Codex Core Agents team builds the agent harness that turns model capability into real-world action. We own the systems around the model: prompting and interpreting model outputs, executing actions safely in real environments, and feeding production experience back into better models and better agent behavior. This team sits close to research and works across the stack: harness, model interaction, inference, sandboxed execution, orchestration, evals, production reliability, and the performance envelope around tokens, latency, cost, capacity, and quality. The harness is open source and increasingly part of how models are trained and evaluated, making this one of the highest-leverage layers in Codex. About The Role We’re looking for engineers to build the AI systems that make Codex agents dependable in production. The ideal candidate is an agent-systems builder: hands-on across low-level systems and ML workflows, able to debug Codex behavior end to end across the harness, model behavior, inference/runtime stack, GPU fleet, and product surface. You’ll work with research, infrastructure, and product to design agent harness capabilities, run experiments and ablations across the model + system prompt + harness stack, build frameworks for assessing production agent performance, and turn messy failures into durable improvements. What You’ll Do Design and build the core agent harness and execution loop that lets Codex agents interpret model outputs, use tools, execute code, and complete long-horizon tasks safely. Build sandboxing, isolation, orchestration, state, and workflow infrastructure for agents operating in real development environments. Develop evaluation, experimentation, and debugging systems that distinguish harness issues, model behavior, inference/runtime issues, and product failures. Run ablations across prompts, model-facing interfaces, context construction, tool-use strategies, and harness behavior to

About the Team Training Runtime designs the core distributed machine-learning training runtime that powers everything from early research experiments to frontier-scale model runs. With a dual mandate to accelerate researchers and enable frontier scale, we’re building a unified, modular runtime that meets researchers where they are and moves with them up the scaling curve. Our work focuses on three pillars: high-performance, asynchronous, zero-copy tensor and optimizer-state-aware data movement; performant, high-uptime, fault-tolerant training frameworks (training loop, state management, resilient checkpointing, deterministic orchestration, and observability); and distributed process management for long-lived, job-specific and user-provided processes. We integrate proven large-scale capabilities into a composable, developer-facing runtime so teams can iterate quickly and run reliably at any scale, partnering closely with model-stack, research, and platform teams. Success for us is measured by raising both training throughput (how fast models train) and researcher throughput (how fast ideas become experiments and products). About the Role As a Training Performance Engineer, you’ll drive efficiency improvements across our distributed training stack. You’ll analyze large-scale training runs, identify utilization gaps, and design optimizations that push the boundaries of throughput and uptime. This role blends deep systems understanding with practical performance engineering — analyzing GPU kernel performance, collective communication throughput, investigating I/O bottlenecks, and sharding our models so we can train them at massive scale. You’ll help ensure that our clusters are running at peak performance, enabling OpenAI to train larger, more capable models with the same compute budget. This role is based in San Francisco, CA. We use a hybrid work model of three days in the office per week and offer relocation assistance to new employees. In this role, you will: Profil

About the Team Our team analyzes inference stack performance across the application, model, and fleet layers to identify bottlenecks and drive faster, cheaper inference. We combine systems profiling, benchmarking, and analysis to understand where time and cost are spent, then turn that understanding into performance optimizations and models that project performance and capacity needs for future launches. About the Role In this role, you will model inference performance across application, model, and fleet layers with higher fidelity. You will build cost-to-serve estimates from microbenchmarks and create tools that help cross-functional teams reason about latency, capacity, utilization, and cost tradeoffs. In this role, you will Build and refine performance models that translate microbenchmark results into cost-to-serve estimates. Analyze inference workloads end to end across applications, models, and fleet infrastructure. Enhance tooling to identify bottlenecks across layers for latency and throughput. Partner with other teams to turn performance insights into concrete improvements and project how future changes affect inference. You might thrive in this role if you: Enjoy reasoning from first principles about distributed systems, model inference, and hardware efficiency. Are comfortable working across abstraction layers, from application behavior to kernels, accelerators, networking, and fleet scheduling. Have deep expertise with performance profiling, benchmarking, analysis, and optimization. Enjoy collaborating with engineering and research teams to improve real production systems. 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 o

About the Team Life sciences is one of the clearest areas where advances in intelligence can meaningfully benefit the world at large. The OpenAI Life Sciences team works at the intersection of advancing frontier life sciences model capabilities and building products to help scientists accelerate their research and leverage the full potential of AI for scientific work. Rosalind Workbench brings together the scientific tools, data sources, interactive biology file viewers and core life sciences workflows into a central environment to help scientists investigate questions, design experiments, analyze results, and advance discovery. Rosalind Workbench can be used with any OpenAI model, including GPT-Rosalind--our dedicated life sciences model, which combines frontier reasoning with specialized tool orchestration across medicinal chemistry, genomics, wet-lab assistance, and other scientific applications. Our long term vision is for teams of agents to work together across these domains, giving researchers access to broader expertise and the ability to pursue more ambitious scientific questions. About the Role We’re looking for a Product Manager to shape Rosalind Workbench for life sciences. You will own product strategy and execution, working directly with researchers in academic labs, biotech, and pharma to understand where AI can meaningfully improve their work. You’ll partner with engineering, research, design, and customer-facing teams to turn emerging capabilities into intuitive products that scientists return to. This role calls for strong product judgment, depth in life sciences, and the ability to move from an ambiguous research problem to a focused, shippable experience. In this role, you will have the opportunity to define the future of AI guided scientific discovery and build the capabilities and tools that help advance the scientific frontier for researchers and help increase the accessibility of model intelligence for scientific use. This is a chance to shape

About us EVERY™ is a leading VC-backed food tech ingredient company and market leader using precision fermentation to create animal proteins without the animal for the global food and beverage industry. EVERY™ is a team of passionate change-makers who are reimagining the factory farm model with a kinder, more sustainable alternative. Leveraging precision fermentation to produce hyper-functional and one-to-one replacement proteins from microorganisms, EVERY™ is on a mission to decouple the world’s proteins from the animals that make them. We are a passionate, determined (and fun!) team with a vital objective, and we're on the lookout for like-minded people to join our mission. For more information, visit www.every.com The Downstream Process Engineer II will be an integral member of our downstream process development team. You will use experimentation to optimize Every’s production process and then see the results of your changes in action at pilot and commercial-scale biomanufacturing sites. This is an excellent opportunity for someone with laboratory and tech transfer experience, who wants to make an impact at scale. What you'll Accomplish Optimize the Every downstream process via an iterative cycle. Improvements are developed in the laboratory, scaled up to an external pilot plant, and learnings are taken back to the lab for further troubleshooting and improvement. Perform various unit operations at the Every HQ such as TFF, depth filtration, chromatography, spray drying and other purification/separation processes. Develop and review tech transfer documentation to ensure successful scale up trials. Travel to external pilot plants to review the scale up of novel processes. Coordinate with third parties such as pilot scale equipment vendors to arrange internal and external trials. Partner with Every scientists and engineers to bring their bench ideas to pilot scale. Analyze results and report data to enable appropriate interpretation and

About us EVERY™ is a leading VC-backed food tech ingredient company and market leader using precision fermentation to create animal proteins without the animal for the global food and beverage industry. EVERY™ is a team of passionate change-makers who are reimagining the factory farm model with a kinder, more sustainable alternative. Leveraging precision fermentation to produce hyper-functional and one-to-one replacement proteins from microorganisms, EVERY™ is on a mission to decouple the world’s proteins from the animals that make them. We are a passionate, determined (and fun!) team with a vital objective, and we're on the lookout for like-minded people to join our mission. For more information, visit www.every.com The Role: This unique entry-level Research Associate I position offers the rare chance to work across two core teams, Analytics and Protein Science. You’ll gain hands-on experience supporting protein development, purification, and analysis, while learning how these disciplines work together to drive innovation in precision fermentation. This is a great opportunity for someone early in their career who thrives in the lab, loves variety, and wants to learn fast in a collaborative, mission-driven environment. What you'll accomplish Generate data through basic biochemistry/molecular biology techniques (including but not limited to BCA, SDS-PAGE) Operate and maintain analytical equipment (e.g., HPLC-UV/RI and Combustion Analyzer, dynamic light scatterer, FPLC-UV, fluorescence/UV plate reader) Support protein characterization workflows through lab-scale protein powder generation involving bench-scale downstream processing unit operations (microfiltration, ultrafiltration, diafiltration) Prepare samples, reagents, and buffers to support cross-functional experiments Collaborate with scientists and engineers across teams to troubleshoot and iterate quickly as part of our Design, Build, Test, and Learn pipeline Present results

About the Team Compute Foundations builds the software that manages OpenAI’s GPU compute infrastructure across sites, data centers, and infrastructure providers, supporting model training and inference. Our systems turn large, heterogeneous fleets of machines into dependable compute for research and products. We build Kubernetes-based control planes, controllers, services, and APIs that coordinate the lifecycle of machines and clusters. We connect global infrastructure management with the realities of bare-metal systems, giving clients consistent interfaces across differences in hardware, topology, and provider behavior. About the Role You will build distributed systems that provision, configure, and manage compute throughout its lifecycle. Your work will connect global services and Kubernetes controllers with the systems that bring machines online, update them safely, and recover them when something goes wrong. This role combines software architecture with an understanding of how machines and data centers work. You might design a lifecycle API, improve controller performance under high concurrency and provider rate limits, or trace a provisioning failure from an API through reconciliation to network boot or host configuration. You will help these systems remain reliable as the fleet expands across sites and generations of GPU hardware. We value depth in relevant systems and the ability to connect layers. You do not need to arrive as an expert in every component of the stack. In this role, you will: Design, build, and operate Kubernetes-based controllers and distributed services that coordinate infrastructure across sites, isolate failures, and scale as GPU capacity grows. Define APIs and resource models that let clients request and track lifecycle operations through consistent interfaces across hardware platforms and providers. Build provisioning and configuration services that coordinate network boot, hardware management interfaces, and the deployment of firmware,

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. Our Payments Risk team builds and operates decisioning capabilities across Signal and Guarantee. We help customers tune thresholds and rules so they can approve more good transactions while reducing returns. For Guarantee, this work also protects the economics of the risk Plaid underwrites. You will be the technical, customer-facing Payment Risk Consulting Lead for Signal and Guarantee. You will interpret model outputs, diagnose customer performance, and turn that analysis into concrete threshold and rules recommendations. You will own proofs of concept and retros, improve existing integrations, and help the team identify patterns that can be scaled through better processes and product capabilities. Responsibilities Own customer proofs of concept and retros from analysis through recommendations and follow-through. Proactively optimize Signal customers, prioritizing accounts with high return rates. Read model outputs and diagnose the drivers of authorization and return-rate performance. Recommend threshold and rules changes that align with each customer's risk and authorization goals. Help Guarantee customers tune thresholds to achieve target authorization rates while protecting lo

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 Manufacturing Engineers to lead the development of processes, tooling, and prototype builds for custom motors and actuators. You will own a primary area as a Stator Process / Manufacturing Engineer, Tooling / Fixture Engineer, or Prototype Manufacturing Engineer, taking that work from early development through validation and repeatable execution in close partnership with mechanical, electromagnetic, electrical, test, quality, and supplier teams. These roles focus on the development, integration, and validation of electromechanical manufacturing capabilities, including stator winding processes, assembly and inspection tooling, and actuator prototype builds. You will help translate engineering designs into reliable hardware while establishing scalable processes, equipment, and build practices for future robotic platforms. This role is based in San Francisco, CA, and requires in-person presence 5 days a week. In this role, you will Each opening focuses on one of the three specialties below, with shared responsibility for reliable processes and hardware. Stator Process / Manufacturing: develop and validate stacking, winding, termination, and potting processes. Establish process parameters, work instructions, and defect controls that produce consistent results across trained operators. Tooling / Fixture: design and deliver winding tools, assembly fixtures, inspection gauges, and bench equipment, from CAD and drawings through fabrication, commissioning, and troubleshooting. Improve setup time, labor, and repeatability. Prototype M

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. The Fraud Data team at Plaid builds the machine learning systems that power Plaid’s fraud detection products, leveraging insights from across Plaid’s network to help identify and stop fraud before it happens. Our team works across the full data science and machine learning lifecycle—from discovering new signals and experimenting with models to deploying and optimizing them in production. We continuously learn from real-world model performance and customer feedback to improve our systems and develop new ways to protect customers and consumers from evolving fraud threats. As a Senior Machine Learning Engineer on Plaid's Fraud Data team, you will develop models that improve fraud detection for our customers. You will identify predictive patterns in Plaid's network data and lead projects from initial experiments through model deployment and ongoing improvement. Investigate fraud patterns and model errors to identify new signals, improve detection, and expand coverage across customers and use cases. Develop training datasets and predictive features, addressing challenges such as incomplete labels, class imbalance, data leakage, and changing fraud behavior. Design, train, and tune model

About the Team The Emerging Products team is a lean, high-output product lab group that builds products at the forefront of model capabilities. We collaborate across all teams within the company, from research and infrastructure to consumer products. The team is responsible for identifying new product opportunities, building them quickly, dogfooding them internally, and then launching the successful products to users. We use data, user research, and analytics to inform our ideas, and make decisions on what experiments are worth iterating, stopping, or scaling. About the Role We’re looking for a senior, product-minded software engineer to own ambiguous 0-to-1 work from idea through prototype, validation, and handoff. This is a full-stack role with a strong frontend and product emphasis: you will build the interfaces and supporting backend systems needed to test new experiences quickly, while making sound architectural choices that enable successful concepts to scale. This role is based in our Mission Bay office in San Francisco. In this role, you will: Build and ship high-quality, product experiments across the full stack. Turn ambiguous user needs and emerging technical capabilities into testable product concepts, using research and metrics to guide iteration. Own technical direction for 0-to-1 projects, balancing speed, reliability, and a clear path from prototype to scalable product. Partner closely with design, product, research, and engineering teams to dogfood, evaluate, launch, and transition successful experiments. You might thrive in this role if you: Have a track record of building and shipping end-to-end products in fast-moving, startup, founder-led, growth, or other high-ownership environments. Bring strong frontend engineering skills and enough backend and systems depth to make sound full-stack architectural decisions. Pair product intuition with evidence, using user research and product data to identify opportunities and make pragmatic tradeoffs. Operat

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 Mechanical Design Engineer to lead the development of motor mechanical designs and prototype hardware for advanced robotic systems. You will own stator and rotor mechanical development from early concepts and detailed design through hands-on builds and prototype validation, partnering closely with electromagnetic, electrical, test, and manufacturing teams. This role focuses on the design, integration, and validation of motor components and prototype processes, including laminations, stack assemblies, bobbins, winding interfaces, and fixtures. You will help drive motor development from initial design through repeatable low-volume builds while establishing the tooling, work instructions, and validation practices needed 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 Own stator and rotor mechanical designs and released CAD and drawings, including geometry, interfaces, fits, tolerances, retention, assembly access, and mechanical validation. Develop laminations, stack assembly methods, bobbins, and winding interfaces that control alignment, insulation, conductor placement, and end-turn packaging. Design, fabricate, and debug fixtures for winding, stacking, assembly, alignment, and inspection. Build and troubleshoot prototypes. Use measurements, defects, rework, and assembly effort to improve designs and processes. Establish low-volume prototype production with equipment, build sequences, work instructions, revision control, traceability

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 Mechanical Engineer to design, build, and own the mechanical side of our robotic actuator dynamometer and test infrastructure. You will create the test stands, couplings, fixtures, load paths, guarding, and serviceable lab hardware that enable rigorous characterization of robotic actuators. This role combines precision mechanical design with hands-on lab work. You will take robotic actuator test infrastructure from requirements and analysis through CAD, fabrication, assembly, commissioning, and iteration, partnering closely with electrical and software engineers to deliver safe, flexible, high-uptime test cells. In this role, you will Own the mechanical architecture of dynamometer and actuator test cells, including frames, bases, load paths, alignment, guarding, and serviceability. Design dynamometer structures, robotic actuator fixtures, load-motor mounts, couplings, shafts, bearings, adapters, and torque-reaction hardware. Translate robotic actuator test requirements into robust mechanical systems for torque, speed, thermal, durability, backdrive, efficiency, and failure testing. Perform first-principles analysis and simulation for stiffness, strength, fatigue, vibration, thermal growth, critical speed, and safety factors. Create precise, repeatable alignment strategies that protect test articles, load machines, sensors, and couplings. Design modular fixturing that supports rapid changeover across actuator and motor variants without compromising measurement quality. Work closely with electrical engineers on cable routing

About ElevenLabs ElevenLabs is an AI research and product company transforming how we interact with technology. We launched in January 2023 with the first human-like AI voice model. Today, we serve millions of users and thousands of businesses - from fast-growing startups to large enterprises like Deutsche Telekom and Meta. Our investors are some of the world's most prominent, including Andreessen Horowitz, ICONIQ Growth and Sequoia. We've raised $781M in funding and our last valuation was $11B - multiples of 11, always. We have expanded from voice into three main platforms: ElevenAgents enables businesses to deliver seamless and intelligent customer experiences, with the integrations, testing, monitoring, and reliability necessary to deploy voice and chat agents at scale. ElevenCreative empowers creators and marketers to generate and edit speech, music, image, and video across 70+ languages. ElevenAPI gives developers access to our leading AI audio foundational models. Everything we do is the result of the creativity and commitment of our team - builders doing the best work of their lives. We are researchers, engineers, and operators. IOI medalists and ex-founders. If you want to work hard and create lasting positive impact, we want to hear from you. How we work High-velocity: Rapid experimentation, lean autonomous teams, and minimal bureaucracy. Impact not job titles: We don’t have job titles. Instead, it’s about the impact you have. No task is above or beneath you. AI first: We use AI to move faster with higher-quality results. We do this across the whole company—from engineering to growth to operations. Excellence everywhere: Everything we do should match the quality of our AI models. Global team: We prioritize your talent, not your location. What we offer Innovative culture: You’ll be part of a generational opportunity to define the trajectory of AI, surrounded by a team pushing the boundaries of what’s possible. Growth paths: Joining ElevenLabs means joining a

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’re looking for a Robotics Control Systems Engineer to take on a foundational role within our robotics team. You’ll help architect, implement, tune, and verify the control infrastructure that enables intelligent, reliable, and responsive robot behavior. This is a deeply hands-on role focused on real-time systems, actuation, dynamics, low-level hardware interaction, and whole-robot performance. You’ll spend significant time working directly with robots onsite: debugging behavior, tuning subsystems, running experiments, and providing feedback across mechanical, electrical, and software teams. This role is based in San Francisco, CA, and requires in-person 5 days a week. In this role, you will: Design and implement real-time control algorithms for robotic systems, including motion control, feedback loops, state estimation, actuator control, and subsystem tuning. Define the control architecture from low-level actuators and hardware interfaces through whole-robot behavior and policy. Identify and characterize actuator, hardware, and software parameters through rigorous experimentation, testing, commissioning, and verification. Work with machine learning engineers to implement reinforcement learning models. Collaborate across mechanical, electrical, and software teams to integrate control logic with sensing and actuation hardware. Help inform the mechanical and electrical design to maximize capability and flexibility. Create the control system architecture; determine the correct level of abstraction from actuators all the way up to whole-robot