Product And Privacy Counsel in San Francisco

About the Team: OpenAI's mission is to ensure that artificial general intelligence (AGI) benefits all of humanity. Our API is the industry's most widely adopted AI platform, empowering startups, indie developers, and Fortune 500 companies alike. Through multimodal APIs—spanning real-time interactions, text-to-speech (TTS), speech generation, and image generation—we enable users to harness the full potential of diverse AI modalities effectively and at scale. About the Role: We are seeking an Engineering Manager to lead our multimodal API product suite. Your team will be responsible for delivering innovative APIs across real-time processing, speech transcription, speech generation, and image creation. You will own the product roadmap for how we evolve our multimodal API offerings, and you will build the products that allow developers to reach millions of end users through AI audio, video, and images. In this role, you will: Build, mentor, and grow a high-performing engineering team focused on multimodal API products – including our realtime API, our transcription models (Whisper), our speech generation models (TTS), and our image generation APIs (DALLE and native 4o). Collaborate closely with product managers, designers, and other stakeholders to define the strategic vision and product roadmap. Work closely with our research teams to improve our core multimodal models for API customer use cases. Guide technical and architectural decisions, emphasizing scalability, robustness, and user experience. Foster a culture of innovation, continuous improvement, and accountability within your team. Qualifications: Proven experience managing engineering teams that deliver complex, high-quality products at scale. Strong technical background and proficiency in modern software engineering practices and system architecture. Excellent collaboration and communication skills to effectively coordinate across diverse teams and stakeholders. Familiarity with or strong interest in multimoda

About the Team: The Database Systems team specializes in high-performance distributed databases. Our team built Rockset, the real-time search, analytics, and vector database that powers all vector search and retrieval augmented generation (RAG) at OpenAI. In addition to retrieval, as an online database, Rockset powers core functionality across all of OpenAI's product lines and many critical internal use cases. About the Role : We are looking for engineers passionate about distributed systems, close-to-the-metal performance optimization (our core engine is written in C++), and building scalable database infrastructure from the ground up. As an engineer on the Database Systems team, you'll contribute to the core database engine, driving improvements across ingestion, query execution, indexing, and storage. You'll partner with teams across OpenAI to unlock new product capabilities and help scale online database reliability and throughput as usage grows by orders of magnitude. In this role you will: Design, build, and operate high-performance distributed systems Identify and resolve performance bottlenecks to scale infrastructure to the next order of magnitude Define long-term technical direction and guide system evolution Collaborate with product, engineering, and research teams to deliver scalable and reliable infrastructure Dig deep into complex production issues across the stack Contribute to incident response, postmortems, and best practices for system reliability You might thrive in this role if you: Have significant experience building, scaling, and optimizing distributed systems at scale Are curious about database internals, storage engines, or low-latency query systems Enjoy debugging challenging performance issues in complex, high-throughput systems Have experience operating production clusters at scale (e.g., Kubernetes or other orchestration systems) Think rigorously about scalability, correctness, and reliability Thrive in fast-paced environments with high

About the Team Business Marketing at OpenAI helps companies understand, adopt, and realize value from intelligence at work. We believe our own marketing organization should demonstrate what changes when intelligence becomes part of the work: fewer manual handoffs, faster learning, better use of customer and product signals, and more capacity for ambitious thinking. Marketing Technology works across Marketing, go-to-market, Data, Engineering, IT, Security, and Product to define the systems, agents, data, workflows, and operating model that power modern marketing at OpenAI. The team has an opportunity to rethink marketing operations alongside the people building the models, products, and infrastructure shaping the future of AI. About the Role We are hiring a Head of Marketing Operations & Technology to build the most AI-enabled marketing operations organization in the world. You will own the systems, infrastructure, data, and workflows that help Marketing operate with greater intelligence, speed, and impact. You will set the function’s strategy, decide what to build or buy, and develop new capabilities where existing solutions fall short. This role sits at the intersection of marketing, technology, data, and AI. You will partner closely with Engineering, Product, Sales, Growth, and Revenue Operations while building a team of technical operators and builders who can turn ambitious ideas into dependable systems. We welcome varied backgrounds—from marketing operations leaders who have expanded the function’s traditional boundaries to founders and builders of AI-native products, growth infrastructure, or internal platforms. What matters most is a deep understanding of marketing, strong technical instincts, and the ambition to imagine a fundamentally better way of working. In this role, you will: Define the vision, strategy, and operating model for Marketing Operations & Technology, including how AI should reshape the function. Build and lead a team spanning market

About the role We’re looking for an engineering manager to lead a team building software systems that detect and prevent harmful misuse of frontier AI models—before incidents occur. This is a builder’s role: you’ll lead engineers shipping production services, detection pipelines, and mitigation mechanisms that protect frontier model integrity and reduce high-severity misuse risk. While this work intersects with frontier model development, security and risk, we’re explicitly seeking someone with a software engineering foundation who is comfortable building reliable systems that can operate at billions of users scale. In this role you will: Lead a team of software engineers building detection + mitigation systems for frontier model misuse, with an emphasis on model IP protection / distillation detection and emerging risk surfaces from autonomous agents. Set the technical roadmap and execution strategy: prioritize, design, ship, iterate, measure impact. Build production systems: services, pipelines, tooling, instrumentation, and automation that scale with frontier model usage. Partner deeply with Research and Product to translate evolving model capabilities into concrete tests, signals, and mitigations that can be deployed at scale. Drive strong engineering fundamentals: architecture, reliability, monitoring, performance, and operational excellence. Hire and grow an exceptional team across backend, data systems, and applied ML engineering domains as needed. Anticipate what breaks at scale as agentic workflows become more capable. You might thrive in this role if you: Experience building systems in adversarial, fast-evolving environments Are comfortable with ambiguity and novelty Have experience adjacent to security (e.g., abuse prevention, fraud, integrity, platform defense, auth/identity, malware/spam, adversarial environments) Communicate clearly and build trust quickly with senior stakeholders—pragmatic, collaborative, and calm under scrutiny. Significant experience

About the Team OpenAI’s AI Success Engineer team partners with the world’s most ambitious organizations to translate cutting edge AI into real business value. We guide customers from first deployment through scaled enterprise adoption. Our work spans technical integration and enablement, workflow transformation, and sustained program and product delivery. Our customers range from fast growing digital natives to the largest global enterprises, government agencies and educational institutions. Every engagement is an opportunity to shape how AI changes work, productivity, and innovation. This role sits at the center of that mission. About the Role The Success Engineer role is the primary post-sales point of contact for a portfolio of education institutions. You are responsible for driving account health and adoption, ensuring technical readiness, identifying high-impact academic and administrative use cases, and delivering measurable value to our education customers using OpenAI’s platform. This role blends technical leadership, program management, customer advisory, and product influence. You will partner deeply with customer teams, map workflows, lead configuration and enablement, oversee deployment plans, and guide institutions toward high impact use cases that showcase the full value of our platform. You will work closely with Sales, Solutions Architecture, Product, and Research to ensure the customer experience is connected and successful across every touchpoint. Success in this role means accelerating adoption, increasing customer activation depth, guiding strategic use cases that get to production, and helping customers demonstrate tangible business impact. This role is based in SF or NYC; we offer relocation benefits to new hires. In this role, you will: Lead the technical relationship for post-sale customers and act as their trusted advisor on deployment, adoption, and value realization Own account health, adoption velocity, and ongoing technical deployment an

About the Team The Support team is central to ensuring that our customers' experience with our products is nothing short of exceptional. We resolve complex issues, provide technical guidance, and support customers in maximizing value and adoption from deploying our products. We work closely with Sales, Technical Success, Product, Engineering and others to deliver the best possible experience to our customers at scale. OpenAI's customers represent a range of diverse backgrounds and maturity, from early-stage startups to established global enterprises. Given OpenAI’s breakneck shipping cadence and growth – and the expectation that it will only accelerate – our ability to architect automation systems and agentic workflows for scale is central to our ability to maintain exceptional support quality in the face of AGI. About the Role As a Support Vendor Manager, you will own the health, performance, and long-term scalability of multiple support partner and vendor relationships. This is a vendor leadership role first and foremost: you will drive commercial and operational accountability (SLAs, QBRs, escalation paths, remediation plans), while also building the operating model that enables support to scale without linear headcount growth. You’ll collaborate closely with User Operations teams (e.g., Trust & Safety, Fraud & Risk), Systems/Tooling, Data partners, and Product/PM stakeholders as we launch new workflow and launch and scale new programs. You’ll be responsible for: End-to-end vendor leadership: Own day-to-day oversight, relationship health, and executive-level accountability for multiple support vendors/BPOs. Performance management & remediation: Define and manage SLA/KPI performance expectations, run WBRs/QBRs, identify performance gaps, and drive structured turnaround plans with clear owners and timelines. Escalation and risk management: Serve as the primary escalation point for vendor issues, including incident response, surge events, quality regress

About the Team OpenAI’s mission is to ensure that artificial general intelligence benefits all of humanity. A majority of our users interact with our products in languages other than English, and our products must work seamlessly across languages, regions, and cultures. The Internationalization team builds the infrastructure that enables OpenAI products to ship globally by default. We develop the systems that power localization, international product launches, and high-quality global user experiences across all OpenAI products. About the Role As a Senior Software Engineer on the Internationalization team, you will build the systems that power localization and international product launches at OpenAI. You’ll work on the platform that manages product content, translation workflows, and localization infrastructure across our products. This role sits at the intersection of AI systems, developer platforms, and product infrastructure. In this role, you will Build and scale OpenAI’s localization, content, and experimentation platform used across OpenAI product teams, including open-source components: Develop AI-powered translation pipelines combined with human-in-the-loop review workflows. Design systems that reliably deliver localized product content across web and mobile apps. Build tools that enable linguists and localization teams to review and improve translations. Develop developer tooling that simplifies localization and internationalization workflows. Build and maintain internationalization libraries used across OpenAI products: Design systems that correctly handle numbers, currencies, dates, and pluralization across locales. Improve support for multilingual interfaces and right-to-left languages. Partner with product teams to improve the international readiness of new features. You might thrive in this role if you Have strong software engineering experience building backend or full-stack systems. Have familiarity with Java, React, MySQL, and cloud infrastructure p

About the Team The Personalization-Memory team, within OpenAI's broader Personal AGI organization, is focused on developing agents that can learn from prior interactions in order to become more helpful and efficient over time. We build general-purpose memory and personalization capabilities that transfer across ChatGPT and other agentic products, and we collaborate with applied engineering on the product surfaces that allow users to interact with memory. About the Role As a Research Engineer / Research Scientist on the Personalization-Memory team, your work will span memory architecture, post-training, and developing long-horizon tasks for training and evaluations. We're looking for individuals who have a background in reinforcement learning research, are able to iterate quickly, and who can convert scientific rigor and long-term research into realized product impact. 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: Own and pursue a research agenda for improving long-horizon memory and personalization in frontier models. Build robust evaluations for tracking modeling improvements. Design, implement, test, and debug code across our research stack. Collaborate closely with the research and product teams to influence the shape of technical solutions in the product. You might thrive in this role if you: Love being on the cutting edge of RL and frontier model research. Value principled approaches and research craftsmanship. Are passionate about long-horizon tasks, memory, and turning your research into product impact. Are comfortable diving into a large ML codebase to debug. Thrive in a fast-paced, dynamic, and technically complex environment. 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 syst

About the Team: Compute Infrastructure builds the platform that turns enormous amounts of compute into a reliable engine for frontier AI. We design, provision, schedule, operate, and optimize the systems that connect accelerators, CPUs, networks, storage, data centers, orchestration software, agent infrastructure, developer tools, and observability into one coherent experience for researchers and product teams. Our work spans the entire stack: capacity planning and cluster lifecycle, bare-metal automation, distributed systems, Kubernetes and scheduling, deep system optimization, high-performance networking, storage, fleet health, reliability, workload profiling, benchmarking, and the developer experience that lets teams use enormous compute systems with confidence. At this scale, small improvements to communication, scheduling, hardware efficiency, or debugging workflows can compound into meaningful research velocity. We are hiring across Compute Infrastructure rather than for a single narrow team, and we use this opening to match strong engineers to the problems where they can have the most leverage. About the Role We are looking for engineers who want to build the compute platform behind OpenAI's research and products. You may not be the strongest in low-level systems, high-performance computing, distributed infrastructure, reliability, CaaS, agent infrastructure, developer platforms, tooling, or the user experience around infrastructure. What matters is that you can reason carefully about complex systems, write durable software, and raise the quality and velocity of the people around you. Depending on your background and interests, you might work close to hardware, close to users, on CaaS and agent infrastructure, or on the control planes and data planes in between. You could help bring new supercomputing capacity online, optimize training workloads from profiler traces and benchmarks, improve NCCL and collective communication behavior, reason about GPUs, NICs, t

About the Team OpenAI's Industrial Compute organization is responsible for planning, delivering, operating, and optimizing the compute infrastructure that powers frontier AI. As OpenAI scales toward becoming an intelligence utility, Industrial Compute coordinates a complex lifecycle spanning infrastructure strategy, capacity planning, provider partnerships, fleet operations, product demand, and financial planning. The organization manages one of the largest and fastest-growing compute footprints in the world, where decisions around capacity allocation, deployment readiness, utilization, reliability, and product demand directly impact product availability, customer experience, and business performance. The Capacity Systems team builds the software platforms, data systems, and automation frameworks that connect these functions into a shared operating model. We transform fragmented planning workflows into scalable systems that enable teams to understand what compute was contracted, delivered, healthy, allocated, and ultimately converted into business and research outcomes. About the Role We are seeking a Capacity Systems Software Engineer to build the platforms and services that power Industrial Compute planning, forecasting, optimization, and operational decision-making. In this role, you will design and develop software systems that connect infrastructure delivery, fleet health, capacity allocation, demand forecasting, deployment readiness, financial planning, and product consumption into a unified system of record. Your work will help OpenAI make better decisions about where compute should be deployed, how capacity should be allocated, and how infrastructure investments translate into business value. You will partner closely with Capacity Planning, Fleet Operations, Infrastructure Engineering, Product, Finance, Supply Chain, and Strategic Sourcing teams to replace spreadsheet-driven workflows with scalable software systems that enable visibility, automation, and dec

About the Team The Demo Studio is responsible for translating OpenAI’s most advanced capabilities into tangible, high-impact experiences for customers. We design and deliver the demos, applications, and environments that define how executives understand what is possible with AI. Our work sits at the intersection of product, engineering, design, and go-to-market. We operate as a hybrid of product studio and live production team, building experiences that are both technically credible and narratively compelling. About the Role We’re looking for a Demo Studio Lead to own the end-to-end demo experience for OpenAI’s major events, webinars, and strategic programs. This is a highly cross-functional role focused on translating cutting-edge AI capabilities into clear, compelling, and production-ready experiences. You will own the full demo portfolio for an event or initiative, spanning mainstage moments, breakout experiences, booths, and supporting content. You’ll define the narrative, architect workflows, build high-fidelity demo environments, direct presenters, and ensure flawless execution in live environments. This is not a traditional sales engineering, presentation, or narrowly scoped design role — it requires a combination of product thinking, technical fluency, storytelling, systems design, and operational excellence. A key part of the role is presenting the work directly: delivering live demonstrations to executive, technical, and industry audiences across mainstage, breakout, customer, and recorded settings. This role is ideal for someone who thrives in ambiguity, operates with strong ownership, and is excited about shaping how the world experiences AI firsthand. This is a hybrid role that can be based in either San Francisco or New York. In this role, you will: Own the end-to-end demo experience across OpenAI-hosted summits, webinars, third-party industry events, and strategic executive demonstrations. Translate approved product positioning, real OpenAI capabiliti

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 Lovable , 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 recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We are looking for strong engineers with experience and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. Specifically, you'll be working on Modal's machines layer: the fleet of bare metal and cloud hosts that every Function, Sandbox, and training job runs on, and the control plane that provisions, images, monitors, and repairs them. You'll automate the integration of new capacity from a growing set of hardware providers; from auditing and benchmarking hosts and clusters, to maintaining our machine images, configuring GPUs, RDMA, networking, and storage, and getting machines into production. You'll build the automation that keeps the fleet healthy without human intervention: detecting bad GPUs, thermals, and disks. You'll dig into whatever is between the hardware and the software that runs on

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 Lovable , 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 recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We are looking for strong engineers with experience and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. Specifically, you'll be working on the distributed object storage system that underpins every container image, volume, and checkpoint on Modal: hundreds of petabytes of data, replicated across multiple cloud object stores and a CDN, cached on local NVMe across a large fleet of workers in many datacenters, and shared peer-to-peer within each datacenter. You'll make cold starts feel local when the data is hundreds of milliseconds away, designing the caching, preloading, and peer-to-peer layers that hide object-store latency and keep public ingress off saturated uplinks. You'll own durability and cost at petabyte scale, from streaming and batch replication between origins, to garbage collecti

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 Lovable , 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 recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We are looking for a strong technical lead to guide the engineers designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. You'll lead the team responsible for the distributed object storage system that underpins every container image, volume, and checkpoint on Modal: hundreds of petabytes of data, replicated across multiple cloud object stores and a CDN, cached on local NVMe across a large fleet of workers in many datacenters, and shared peer-to-peer within each datacenter. You'll set technical direction for the primitives that other teams (filesystems, training, sandboxes) build on, balancing durability, latency, throughput, and cost. You'll own the roadmap from today's hardest problems (garbage collection at petabyte scale, active-active replication, rate limiting that protects the upstream without wasting ut

Work Flexibility: Field-based Stryker Position Title: Foot & Ankle Sales Associate What you will do The Foot & Ankle Sales Associate will partner closely with Sales Representative(s) in the area to quickly learn the medical device industry and Foot & Ankle business, and then contribute to the growth of that business in the assigned territory. He/she will partner with the Sales Rep(s) in all aspects of the sales call pattern, including but not limited to, covering cases in the assigned territory, marketing and promotion of the products in the assigned accounts, building of sets, managing inventory, and, as they learn and grow, beginning to convert customers to Stryker. Attend surgeries in which Stryker Foot & Ankle products are used, to ensure all products are available for surgeon use in each case and to instruct surgeons regarding product use and functionality. Educate and inform doctors, nurses, and appropriate staff personnel as to the proper use and maintenance of Stryker products, product functionality and updates, changes to product portfolio, and educational programs. Work with sales teams to contact customers in order to identify sales opportunities, deliver excellent customer service, and further develop the customer relationship. Identify the needs of new prospects, in conjunction with the assigned Sales Representative, and develop appropr