Reliability Engineer Iii in San Francisco

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About the Role: The Web Infrastructure team builds the foundations behind Notion’s web clients, including client architecture, performance, reliability, and shared design systems. As Engineering Manager, you’ll lead the team through the evolution from Notion Clients. You’ll set strategy, develop senior engineers and managers, and partner across Notion to make the product faster, more reliable, and easier to build. We work from our offices on Mondays, Tuesdays and Thursdays (our Anchor Days) because we do our best thinking and building together in person. We’re looking for someone who’s excited to work alongside the team during those days. What You'll Achieve: You'll build and manage a diverse and inclusive team of engineers and managers working on core parts of Notion's architecture. You'll create a healthy environment in your team that embodies Notion's values. You'll recruit, coach, and develop engineers. You'll ensure engineers are regularly receiving feedback and making progress on personal and professional goals. You'll facilitate planning—the prioritization, sequencing, and staffing of work—for your team. You'll be responsible

About the Team The People Technology team builds and operates the systems that support how OpenAI hires, develops, and supports its people. The team brings together People Systems and People Innovation Labs, a product engineering group focused on rethinking how we find and retain exceptional talent and help employees do their best work. People Systems owns the company’s core people-technology ecosystem, including platforms such as Workday and Ashby. People Innovation Labs builds new employee and People Team experiences on top of that foundation, including OpenHouse, our internal employee hub, and AI-powered products and automations. Together, we are working toward a model in which our enterprise systems provide reliable data, controls, and core business logic, while employees and managers can complete more of their work through simple, integrated, and AI-native experiences. About the Role We are looking for a People Systems Lead to manage the People Systems team and shape how our core systems evolve. You will be responsible for the reliability and effectiveness of our current environment while helping us move beyond the constraints of traditional enterprise software. This includes stabilizing and improving platforms such as Workday and Ashby, designing the integrations that connect them to the broader technology ecosystem, and partnering with People Innovation Labs to surface workflows through OpenHouse, Slack, and AI-powered experiences. This role requires someone who is comfortable moving between strategy, technical design, and team leadership. You should understand People systems deeply, be able to work through integration and architecture decisions with engineers, and translate complex organizational needs into scalable solutions. You will also manage vendor relationships, develop the People Systems team, and drive alignment across People, Engineering, Finance, Security, Legal, and other partners. This role could be a fit for someone who has grown up in People S

About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a member of Agent Post-Training, you will improve the capabilities, reliability, and product fit of OpenAI's agentic models. You might own a research direction, build the infrastructure that makes large training runs faster and more trustworthy, create evals that reveal where models fail, or drive a capability from an idea through experimentation, integration, and launch. This role is intentionally broad. The strongest candidates are not defined by one method or subfield; they are people who can take an ambiguous capability problem and make progress across research, engineering, data, evals, and product. You should be excited to work on models that act in the world: writing and debugging code, using tools, calling functions, operating computers, collaborating with other agents, and completing valuable work on behalf of users. You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, meas

About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a member of this API & power-users team, you will improve the capabilities, reliability, and product fit of OpenAI’s agentic models for power users and API developers. You might design evals from real developer workflows, build training environments around production-like tool use, turn qualitative model failures into training data, evals, or post-training interventions, or drive a behavior improvement from discovery through post-training, integration, and launch. This role is intentionally broad. The strongest candidates are comfortable turning ambiguous model behavior problems into concrete progress, whether that means improving tool use, planning, instruction following, recovery from mistakes, or how models behave in API-based workflows. You should be excited to work across research, engineering, data, evals, and product to make models better at acting in real workflows. You will work closely with researchers, engineers, API/product teams, Codex, infrastructure, and safety/align

About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a member of Agent Post-Training, Computer Use, you will teach models to operate computers. You will help train models that can navigate browsers and desktops, use tools and applications, reason through complex workflows, collaborate with users and other agents, and complete long-horizon tasks with reliability and judgment. This work sits at the intersection of frontier model training, product behavior, evaluation, and systems engineering, and will directly shape the computer-use capabilities shipped in OpenAI’s next generation of agents. Currently, our models are the best in the world at this behavior! You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people. This is a high-agency role for people who want their work to land directly in frontier models. In this role, you might Design and run experiments th

About the Team The Artifacts team is building the AI-native creation layer for documents, spreadsheets, slide decks, dashboards, reports, analyses, and new forms of interactive work products. We are rethinking what creation looks like when models can move from an ambiguous user goal to a polished, editable artifact with strong structure, taste, correctness, and speed. This is a high-agency team working across product, infrastructure, and research. We partner closely with model training teams to shape how frontier models create artifacts, and with ChatGPT product teams to turn those capabilities into experiences that millions of people can use. The work spans full-stack product engineering, model integration, rendering and editing systems, collaboration, storage, evaluation loops, and production reliability. Our ambition is to build the premier product experience for AI-generated artifacts: starting with familiar work products like slides, sheets, and docs, then expanding into new artifact types that are only possible in an AI-native world. About the Role As Engineering Manager, Artifacts, you will lead and grow the engineering team responsible for building this product and technical foundation. You will manage a team of full-stack and infrastructure-oriented engineers, set technical direction, and stay hands-on enough to shape architecture and debug hard problems. This role sits at the intersection of product engineering, research, and infrastructure. You will partner with researchers on how models are trained and evaluated for artifact creation, with product and design on the user experience. This is a strong fit for a technical manager who wants to build and ship, not only coordinate. The team has a fast trajectory, so you will help define both the product surface and the team that builds it. In this role, you will: Lead, manage, and grow a team building AI-native artifact creation experiences across documents, spreadsheets, slide decks, and emerging artifact form

About the Team OpenAI's Industrial Compute organization is building the world's most advanced AI infrastructure ecosystem. Through strategic partnerships and self-built campuses, we are scaling one of the world's fastest-growing AI infrastructure platforms. The Supply Chain organization ensures critical infrastructure components—from compute systems and networking equipment to integrated rack solutions—are sourced, manufactured, qualified, and delivered with the speed and reliability required to support frontier AI development. We partner closely with Hardware Engineering, Manufacturing Quality Engineering, Infrastructure Delivery, Hardware Operations, Finance, and suppliers worldwide to build a resilient, scalable supply chain capable of supporting rapid infrastructure expansion. As Industrial Compute continues to grow, Supply Chain serves as the operational bridge between engineering innovation and large-scale infrastructure deployment. About the Role We are seeking a Supply Chain Manager to lead strategic execution across sourcing, supplier operations, manufacturing quality, and infrastructure delivery for OpenAI's AI infrastructure portfolio. This role will oversee a multidisciplinary team responsible for strategic sourcing, manufacturing quality engineering, and technical program management while partnering closely with engineering, finance, hardware operations, and deployment teams. You will drive supplier strategy, manufacturing readiness, production planning, quality performance, and operational execution across the full hardware lifecycle. Success requires balancing long-term supplier strategy with day-to-day execution. You'll establish scalable operating mechanisms, strengthen supplier partnerships, manage complex cross-functional programs, and ensure OpenAI can rapidly deploy AI infrastructure without compromising quality, cost, or reliability. This is a people leadership role responsible for developing a high-performing organization while driving operati

About the Team The Human Data team at OpenAI is responsible for identifying and mitigating risks in advanced AI systems by designing evaluations, surfacing vulnerabilities, and collaborating closely with researchers to strengthen model reliability and public trust. About the Role As a Research Program Manager, you will lead initiatives that test the safety and robustness of OpenAI’s models through creative experimentation and structured evaluation. You’ll coordinate efforts across research and engineering teams to transform ambiguous risks into concrete research programs and influence future model development and deployment. We’re looking for people who are technically savvy, comfortable with ambiguity, and excited about shaping the future of safe AI. 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: Lead programs that explore unexpected model behaviors and identify failure modes. Translate vague or emergent risk signals into clear priorities and actionable research plans. Design and run creative evaluations, experiments, and red-teaming campaigns. Collaborate with research, product, and deployment teams to integrate findings into model training and deployment cycles. Develop repeatable systems for tracking model performance and understanding emerging behavior patterns. You might thrive in this role if you: Have strong experience in technical program management, with excellent organizational and communication skills. Are familiar with large language models, prompt engineering, or model evaluation techniques. Are comfortable managing fast-paced, high-uncertainty projects and shaping them from the ground up. Are creative and resourceful in devising new methods for testing model behavior and performance. Can effectively coordinate across technical and non-technical stakeholders to drive alignment and execution. About OpenAI OpenAI is an AI resear

About the Team OpenAI’s mission is to ensure that general-purpose artificial intelligence benefits all of humanity. We believe that achieving our goal requires effective engagement with public policy stakeholders and the broader community impacted by AI. Accordingly, our Global Affairs team builds authentic, collaborative relationships with public officials and the broader AI policymaking community to inform and support our shared work in these domains. We ensure that insights from policymakers inform our work and – in collaboration with our colleagues and external stakeholders – seek to shape policy so that it aligns with and supports our mission. About the role OpenAI is looking for an Applied Risk Standards Specialist to lead standards work for applied risk in applications, including mental health, youth safety, age assurance, functional efficacy, reliability, and privacy-related risks. You will help turn internal research, safety policies, and evaluation methods into technically sound, measurable, and adaptable standards that build public trust and support responsible deployment. This role sits within our AI standards and global assurance function in Global Affairs. Working closely with Safety Systems, Research, Product, Model Policy, Legal, and third-party evaluators, you will author proposals, negotiate requirements, and represent OpenAI in priority standards bodies. You will take on the drafting and external engagement needed to advance this work, enabling technical experts to focus on the underlying methods and evidence. You will also bring emerging requirements back into internal planning before they become established expectations. Alongside this primary portfolio, you will support the AI Standards and Global Assurance Lead on frontier AI assurance, contributing to risk-management standards, evaluation and benchmarking requirements, and approaches to independent assessment. The role connects technical practice with external standards. It does not replace t

About the Team The Growth Platforms team builds the systems and operating foundations that help OpenAI grow responsibly. We partner across the product portfolio to connect customer signals, identity and consent, campaign workflows, measurement, and product experiences into an AI-enabled growth engine. Our work helps teams launch, learn, and scale with a high bar for data quality, privacy, reliability, and customer trust. About the Role We’re looking for an experienced marketing technology and operations leader to drive cross-functional work at the intersection of growth, measurement, data, and automation. Your mission will be to turn fragmented tools, signals, and workflows into reliable, measurable, AI-enabled capabilities that teams can use safely at scale. You’ll work across Growth, Marketing Operations, Product, Engineering, Data Engineering, Data Science, Security, Privacy, Legal, and Revenue Operations, as well as external advertising platforms, measurement providers, and implementation partners. You’ll translate business requirements and privacy constraints into data contracts, integration designs, rollout plans, and reliable first-party data systems. This is a hands-on, high-impact role for someone who brings structure to ambiguity and moves from event schemas, APIs, and data quality assurance to operating cadences, partner enablement, and executive updates. This role is based in San Francisco or New York City with a hybrid office expectation. In this role, you will: Own the operating model for Growth’s marketing technology stack across identity, consent, audiences, activation, measurement, and experimentation. Own and operate the complete paid-media tracking and measurement system, including website pixels, server-to-server conversion events, mobile measurement integrations, identity and consent controls, attribution methods, and timely signal delivery to advertising platforms. Design and implement event schemas, data mappings, APIs, and integrations; valid

About the Team The ChatGPT Search Product Infrastructure team builds the foundational systems that power search experiences across ChatGPT. We develop the product infrastructure that connects models with search systems and other sources of real-time information, enabling ChatGPT to deliver timely, relevant, and trustworthy answers to users around the world. Our work sits at the intersection of product engineering, AI, and large-scale infrastructure. We build shared platforms and abstractions that enable product teams to independently develop, evaluate, and launch new search-powered experiences. These platforms provide the guardrails, testing capabilities, observability, and rollout controls needed to prevent reliability, scalability, quality, and latency regressions while supporting rapid product iteration. The team partners closely with: Post-Training on model launches, experimentation, and prompt optimization Search product verticals on new user experiences Inference on GPU efficiencies Indexing and Retrieval on the systems that identify and deliver relevant information Capacity/Fleet team to ensure optimal regionalized provisioning of GPUs and CPUs About the Role We are looking for an Engineering Manager to lead the team responsible for ChatGPT’s Search Product Infrastructure. You will set the technical and organizational direction for the systems that bring search capabilities into ChatGPT. You will guide architectural decisions across search orchestration, model and prompt integration, serving infrastructure, experimentation, observability, evaluation, and product integrations. You will balance immediate launch and product needs with the long-term reliability, scalability, latency, and maintainability of the platform. A central responsibility of this role is creating leverage for Search product verticals. You will lead the development of extensible platforms that allow those teams to independently build, test, and launch features without requiring ongoing invol

About the Team OpenAI's data and storage infrastructure spans data platforms, online databases, and file/object storage. These systems underpin data ingestion and processing, durable persistence, indexing and retrieval, and product file experiences. As frontier models and agents evolve how they use memory, history and snapshots, the underlying architecture increasingly shapes the capabilities products can deliver—and their latency, reliability, cost and efficiency. About the Role We are looking for a technically deep TPM to independently define and lead multiple programs across data platforms, online databases and storage infrastructure. You will connect model, product and data-consumer requirements to architecture, and work with the relevant engineering teams to take new capabilities through production adoption and repeatable expansion. The design scope is exabyte-scale storage and infrastructure spanning multiple millions of CPU cores. The challenge is not simply forecasting more resources: it is making complete, workload-ready capacity repeatable, with a clear path from product requirements through architecture, deployment and validation. A data pipeline, database query, file operation or execution snapshot can affect whether a product or agent succeeds; you will connect those outcomes to the systems underneath. 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: Translate model, product and data-platform needs into precise access patterns, consistency, durability, freshness, availability and scalability requirements. Connect memory, history, retrieval and resumable work to capability and end-to-end latency. Partner with engineering to transform data and storage architecture into repeatable scale units: standardized provisioning, placement, routing, data movement and readiness checks that bring storage, compute and networking online together.

About the Team The Product & Platform teams at OpenAI are responsible for delivering the company’s most impactful offerings—such as ChatGPT, our API platform, and new enterprise capabilities—to a global and diverse customer base. These systems must perform at scale and deliver exceptional experiences to developers, consumers, and businesses alike. The ChatGPT engineering org builds and operates the systems that bring product improvements to users across backend services, web, mobile, and desktop platforms. The Developer Velocity team partners with product engineering, platform, infrastructure, reliability, engineering acceleration, and observability teams to make everyday development faster and releases safer, more predictable, and easier to operate. About the Role We are seeking a Technical Program Manager to improve developer velocity and deployment excellence across ChatGPT. You will lead durable improvements to local development, CI, testing, build systems, release trains, progressive rollout, and post-deployment validation. You will identify the highest-leverage sources of engineering friction, align teams around shared standards and metrics, and drive adoption of tooling and workflows that improve both speed and reliability. This role combines systems thinking, technical program leadership, and hands-on operating rigor across a broad engineering surface. 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 the cross-functional roadmap for improving local development, CI, testing, build workflows, and release infrastructure. Create a durable intake and prioritization mechanism for developer friction, using evidence to focus teams on the highest-impact improvements. Lead programs that improve deployment speed and safety, including pre-merge confidence, progressive rollout, release guardrails, rollback readiness, and post-deploy valida

About the Team The Product & Platform teams at OpenAI are responsible for delivering the company’s most impactful offerings—such as ChatGPT, our API platform, and new enterprise capabilities—to a global and diverse customer base. These systems must perform at scale and deliver exceptional experiences to developers, consumers, and businesses alike. The ChatGPT infrastructure team is responsible for ensuring that our products can serve rapidly growing demand with the performance, reliability, and quality our users expect. This work sits at the intersection of product demand, model deployment, inference, research, fleet, and capacity. The team translates changing product and model needs into clear capacity decisions and safe, scalable launches. About the Role We are seeking a Technical Program Manager to lead the operating system for Chat capacity and model deployment. You will connect demand forecasting and capacity allocation with model readiness, rollout planning, launch coordination, and post-deployment learning. You will also own mode deployment beyond capacity by working with cross functional teams across research, post-training, inference and product to own mainline model deployment. You will bring structure to constrained-capacity decisions, improve the tooling and mechanisms teams use to prioritize demand, and help new models reach users safely and efficiently. Success requires technical depth, sound judgment under ambiguity, and crisp execution across product, research, infrastructure, and operations teams. 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 cross-functional programs for Chat capacity forecasting, allocation, headroom planning, and constrained-capacity operations. Build durable intake, prioritization, and decision mechanisms that connect product demand and model requirements to available serving capacity. Partner

About Team Our Robotics team is focused on unlocking general-purpose robotics and advancing toward AGI-level intelligence in dynamic, real-world environments. Working across the full model and systems 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 physical constraints of real-world systems to improve people’s lives. About the Role We are looking for a Technical Program Manager to own actuator development and integration from system goals through production readiness. The actuator program spans mechanical, electrical, firmware, harnessing, controls, test, reliability, manufacturing, and supply chain, and needs a TPM who can turn cross-functional decisions into clear scope, executable milestones, and timely decisions. In this role, you will help the team converge on the right technical plan, surface risks early, and deliver reliable actuator systems on schedule. This role is based in San Francisco, CA and requires in-person presence 4 days a week. In this role you will: Drive actuator programs end-to-end, aligning scope, milestones, interfaces, dependencies, and exit criteria across engineering teams. Drive scope lock and technical convergence for sprints, MVPs, and stretch goals while connecting component decisions to system performance. Coordinate actuator development across motors, gears, sensing, electronics, and firmware, and align the electrical and mechanical interfaces that connect actuators to the broader robot. Lead validation planning from early prototypes through engineering validation, reliability testing, and production readiness. Drive tradeoff decisions across cost, quality, performance, schedule, and lead time by collaborating cross-functionally and quantifying impact to meet program deliverables. Establish effective mechanisms for technical reviews, change control, design releases, decision tracking, and manufacturing readiness.