It Support Administrator in United States

About the team Platform Partnerships builds and grows the relationships that extend OpenAI products through the world’s most important technology platforms. The team works across Product, Engineering, Research, Go-to-Market, Legal, Finance, Marketing, Policy, and Operations to turn partner opportunities into durable product experiences and business outcomes. We are a small team working on opportunities that rarely arrive with a playbook. We set the strategy, make the tradeoffs, and stay close to execution through launch and scale. About the role We’re hiring a Strategic Partner Manager to own and drive the expansion of a portfolio of OpenAI’s most strategic platform partnerships. You will treat each partnership as a business: set the expansion thesis, align joint product roadmaps, structure commercial opportunities, and translate shared ambition into measurable adoption, usage, revenue, distribution, and product impact. This is a senior individual-contributor role with full-lifecycle ownership—from strategy and negotiation through integration, launch, performance, expansion, and renewal. It is a 0-to-1 builder role, not a coordination role. You will create clarity where the operating model is still emerging, make sound decisions with incomplete information, and step into the details required to move the work forward. The right person can move fluidly between a multi-year partnership strategy and the immediate product, commercial, or operating blocker in front of the team. You will build trusted relationships at the executive and working levels while representing OpenAI’s priorities with clarity and thoughtful pushback. What success looks like Each priority partner has a clear expansion thesis, joint roadmap, governance model, and measurable outcomes. High-priority product integrations and go-to-market initiatives launch with clear ownership, strong readiness, and fewer unresolved dependencies. Partnerships show measurable growth across the outcomes that matter for t

About Taskrabbit: Taskrabbit is a marketplace platform that conveniently connects people with Taskers to handle everyday home to-do’s, such as furniture assembly, handyman work, moving help, and much more. At Taskrabbit, we want to transform lives one task at a time. As a company we celebrate innovation, inclusion and hard work. Our culture is collaborative, pragmatic, and fast-paced. We’re looking for talented, entrepreneurially minded and data-driven people who also have a passion for helping people do what they love. Together with IKEA, we’re creating more opportunities for people to earn a consistent, meaningful income on their own terms by building lasting relationships with clients in communities around the world. Taskrabbit is a hybrid company with employees distributed across the US and EU and a Built In — Best Places to Work (2022, 2023, 2024, 2025) continually ranked across multiple national and regional categories. Join us at Taskrabbit, where your work will be meaningful, your ideas valued, and your potential unleashed! Prior to applying please note: W e are currently unable to provide visa sponsorship for this position (including H-1B, OPT, or other employment-based visas). Candidates must be legally authorized to work in the United States without employer sponsorship now or in the future. This role is hybrid requiring 2 days in office at our San Francisco hub every Tuesday & Wednesday (located at 130 Sutter St). About the Role Machine Learning is a cornerstone at Taskrabbit, and we’re looking for a Staff Machine Learning Engineer to take technical ownership of our core ranking system. Every job request on the platform flows through it, making this one of the most consequential ML systems we run. This is a hands-on technical leadership role. You’ll operate as the primary architect and engineer for the ranking system — defining the system direction, driving the roadmap, solving the hardest problems, and creating leverage for the engi

About the Team The Product Policy team is responsible for the development, implementation, enforcement, and communication of the policies that govern use of OpenAI’s services, including ChatGPT, GPTs, the GPT Store, Codex, and the OpenAI API. About the Role We are looking for a Research and Advisory Partnerships Lead to build and manage the relationships, partnerships, and advisory structures that bring independent external expertise into our product and policy decisions. 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 identify and engage researchers, civil society organizations, subject-matter experts, and other external stakeholders whose perspectives can strengthen how we develop and deploy AI. You will establish and manage advisory councils, develop research partnerships with the academic community, and work closely with internal teams to translate external insights into actionable guidance. This role sits at the intersection of product, policy, research, and governance. It is well suited to someone who is comfortable building relationships across disciplines and designing processes that ensure outside expertise meaningfully informs internal decision-making. This role can be based in San Francisco or New York City. 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: Develop, launch, and manage external advisory councils and other governance mechanisms that provide structured input on product and product policy. Build and maintain relationships with external experts, researchers, civil society organizations, and other stakeholders who can inform high-priority product and product policy decisions. Identify when external consultation can improve internal decision-making, and develop engagement strategies tailored to specific products, policy questions, and emer

About the Team OpenAI’s mission is to ensure that general-purpose artificial intelligence benefits all of humanity. The Identity team builds the foundational systems that enable people, organizations, devices, and agents to securely access OpenAI products. The team works across consumer and enterprise experiences, including account structures, sign-in, authentication, recovery, privacy, permissions, administration, and agent identity. As AI systems become increasingly capable of acting on behalf of people and organizations, we are defining new models for authorization and trust across human-to-agent and agent-to-agent interactions. About the Role In this role, you’ll lead design for foundational identity experiences across OpenAI’s products. You’ll make permissions, access, risk, and administration feel clear, safe, and genuinely usable—whether someone is securing a personal account, administering access across an enterprise, signing in to another product with ChatGPT, or authorizing an agent to perform sensitive work. Your work will span established identity challenges and emerging interaction models without established design conventions. You’ll help define how users understand what an agent can access, who or what it is acting on behalf of, and when confirmation or stronger authentication should appear. Working closely with product, engineering, security, privacy, and design, you’ll translate complex policies and technical systems into coherent, trustworthy experiences. This role is based in our San Francisco HQ. We offer relocation assistance to new employees. In this role, you will: Lead the design direction for identity, account security, permissions, and administrative experiences across OpenAI’s consumer and enterprise products. Design and ship high-quality experiences spanning sign-in, authentication, account recovery, device accounts, privacy, access controls, governance, and remediation. Define mental models and interaction patterns for human-to-agent and

About the Team Enterprise Verticals builds role-specific ChatGPT Work experiences for high-value enterprise workflows. We combine product engineering, plugins and skills, connectors, data, evaluations, and customer evidence to turn useful demos into reliable daily work. This opening sits within the Technology vertical inside Enterprise Verticals. The group focuses on repeatable workflows for people at technology companies, beginning with functions such as data and analytics, sales, and design, and carries the shared platform needs—tool integration, permissions, quality measurement, and safe rollout—across those experiences. We work closely with Design, Research, GTM, Security, and platform teams, as well as with customers and design partners. Success means that people can reach a trustworthy first result, understand what the system did, and keep using the workflow—not merely that a prototype exists. About the Role We are looking for a full-stack product engineer who can own ambiguous enterprise workflows end to end: understand a customer problem, shape the product, build across frontend and backend, work through platform dependencies, instrument quality, and learn quickly with design partners. You will build across ChatGPT Work surfaces, services, plugins, connectors, and data or permission boundaries when the experience requires it. You will make quality and rollout observable through evaluations, product and operational signals, and clear fallback or rollback paths. This is a product-engineering role for someone who can move between user problems and system details without losing ownership of either. The strongest candidates will be able to turn specific customer evidence into a generalizable product, explain scope and architecture tradeoffs, and carry a feature from an early prototype through a bounded production rollout. In this role, you will: Build and ship role-specific workflows across ChatGPT Work surfaces, services, plugins, and connectors. Turn customer a

About the Team The B2B Marketing team is responsible for helping businesses understand, adopt, and get value from OpenAI’s products. B2B marketing is a major and growing priority for OpenAI as we scale our work with companies, developers, and institutions around the world. About the Role Within B2B Marketing, Demand Generation builds the integrated, full-funnel engine that connects audience insights, content, field and digital experiences, paid media, lifecycle, and sales follow-through to qualified pipeline. We partner closely with Sales, Partnerships, Product Marketing, Communications, Creative, Web, RevOps, Analytics, and regional teams to create a cohesive customer experience and scale what works. We’re looking for a Senior Lifecycle Strategist to define how prospects and customers move through personalized, signal-driven journeys across the B2B lifecycle. You’ll own lifecycle strategy, audience and journey architecture, testing priorities, and performance recommendations while partnering closely with a Lifecycle Marketing Manager on build and delivery. Initially, the role will focus on prospect nurture, database activation, and sales handoff; over time, it will help expand our lifecycle capabilities across adoption, cross-sell, upsell, retention, and re-engagement. In this role, you will: Define the B2B lifecycle strategy, journey architecture, audience framework, communication principles, and roadmap across prospect and customer stages. Design nurture and activation programs that respond to fit, persona, segment, product interest, engagement, intent, and sales status rather than relying on one generic journey. Partner with RevOps, Data, Web, SDR, Sales, and Product teams to establish reliable triggers, scoring inputs, routing logic, suppression rules, exits, and service levels. Work closely with the Lifecycle Marketing Manager to translate strategy into clear program requirements, content needs, build plans, QA standards, and launch sequencing. Own the lifecyc

About the Team OpenAI's Professional Services team helps organizations move from AI ambition to durable production outcomes. We partner with customers on complex deployments and build the strategy, commercial models, operating mechanisms, and delivery capacity needed to realize value from OpenAI's models and products. The team works across Go-to-Market, Forward Deployed Engineering, Technical Success, Finance, Product, Legal, Data, Systems, and delivery partners. We are building a services motion that is customer-centered, commercially rigorous, operationally scalable, and deliberately connected to product adoption. About the Role We are seeking a senior GTM Strategy & Operations professional to build and scale the operating system for OpenAI's Professional Services business. This is a foundational, hands-on individual contributor role at the intersection of business strategy, finance, go-to-market, and delivery. You will turn ambiguous questions—what we offer, how we price and package it, how we plan capacity, and how we measure performance—into clear decisions and repeatable mechanisms. You will own business planning, pricing and packaging, forecasting and modeling, management reporting, and cross-functional strategic initiatives. You will build integrated views of demand, staffing, revenue, margin, and delivery performance; replace one-off analyses with durable processes; and create operating cadences that help leaders act early. You will be a trusted partner to Professional Services, GTM, FDE, Technical Success, Finance, Product, Legal, Revenue Operations, and Data leaders. The right person combines direct Professional Services judgment with rigorous analytics, executive communication, and the willingness to build the model, process, or dashboard themselves. You’ll be responsible for: Define and drive the business and GTM strategy for Professional Services, including target customer needs, offer portfolio, positioning, pricing and packaging, partner motions,

About the Team The Systems Integration team is responsible for building the infrastructure, tooling, and validation systems that ensure our device software our device software is reliable, testable, and ready to ship. We design and maintain build systems, CI pipelines, automated test frameworks, and hardware-in-the-loop labs to enable rapid, safe product launches. Our work spans build systems, developer tools, systems integration, and cross-team collaboration to ensure developers can build reliably and ship with confidence. About the Role We are looking for an engineer to help evolve OpenAI’s Consumer Products build and continuous integration systems for a fast-growing engineering organization. This role sits at the intersection of developer productivity, build systems, distributed infrastructure, software quality, and on-device software. You will work on the systems that determine how quickly and confident engineers can move: Bazel-bazed builds, Buildkite pipelines, test coverage, remote caching and execution, CI observability, and tooling that helps engineers understand and fix failures quickly. Our mission is to enable OpenAI to ship software running on consumer devices rapidly with a high bar for correctness, reliability, and safety. The best version of this work is invisible when it succeeds: builds are fast, tests are trusted, CI failures are understandable, and engineers can focus on shipping products instead of fighting infrastructure. This role is based in San Francisco, CA. We use a hybrid work model of four days in the office per week and offer relocation assistance to new employees. In This Role, You Will Own and evolve Bazel and yocto-based build and test workflows in a polyrepo environment Design and maintain Starlark rules, macros, toolchains, and integrations that make builds hermetic, reproducible, and easy for teams to adopt Improve CI performance and reliability across Buildkite pipelines, including queue time, build time, cache hit rates, retry b

About the Team OpenAI’s GTM Data Science team helps shape how our products are adopted, monetized, and scaled across organizations. We work at the intersection of Product, Go-to-Market, Finance, Research, and Data, turning product usage, customer evidence, and market signals into decisions that grow durable enterprise value. We’re looking for a senior Data Scientist to own the analytical strategy for enterprise knowledge-worker adoption. As ChatGPT Work and Codex become capable of research, analysis, document creation, spreadsheets, presentations, internal knowledge synthesis, and other agentic workflows, you will help determine how these products become embedded in everyday work—not merely tried once. About the Role You will define how we measure activation, retained usage, workflow depth, and value across ChatGPT Work, Codex, and connected enterprise systems. You will explain why adoption succeeds or stalls and identify the product, enablement, and commercial interventions most likely to create durable usage. This is a hands-on, zero-to-one role. You will work through imperfect telemetry, overlapping product surfaces, evolving definitions, and ambiguous business questions. You will partner closely with GTM, Product, Finance, Research, Customer Deployment, Analytics Engineering, and Data Science. Your work is successful when it changes a product, GTM, or investment decision. In This Role, You Will Define a trusted measurement framework for knowledge-worker adoption, including identity, eligible populations, activation, retained usage, penetration, workflow depth, feature adoption, and monetization. Map the knowledge-worker journey from initial exposure through first successful task, repeated workflows, multi-surface usage, and durable adoption. Identify which personas, functions, use cases, product capabilities, and account conditions are associated with deep and retained usage. Design and evaluate experiments and quasi-experiments across onboarding, enablement, wo

About the Team The Statsig team within OpenAI builds the experimentation, feature rollout, dynamic configuration, and analytics systems that help OpenAI ship products with speed, safety, and evidence. Our work sits on the critical path for how product, engineering, research, and go-to-market teams learn from real-world usage and make high-confidence decisions. Statsig began as an independent company focused on helping builders move faster through trustworthy experimentation and feature management. After joining OpenAI, the team began its next chapter: bringing deep product expertise, customer intuition, and mature platform infrastructure into the product development system used by every OpenAI team. Today, teams across ChatGPT, Codex, model measurement, consumer monetization, business subscriptions, developer products, and shared infrastructure rely on Statsig to safely introduce new capabilities, measure impact, and roll changes forward or back with confidence. We are at a defining moment as adoption accelerates and the platform becomes a company-wide standard. About the Role We are looking for an Engineering Manager, Statsig Product to lead the product engineering organization responsible for Statsig’s post-acquisition journey at OpenAI. You will define how experimentation, rollout, configuration, and analytics become a simple, reliable, and trusted part of how every OpenAI product team ships. You will set strategy across multiple product and platform workstreams, build the organization and leadership structure needed for the next phase, and establish the operating model for a platform that serves teams across the company. The right leader can operate across product strategy, technical architecture, organizational design, developer experience, reliability, and executive alignment. You will help preserve what made Statsig strong while integrating it deeply into how OpenAI launches, measures, learns, and makes product decisions. In this role, you will: Build, lead,

About the team The Applied team safely brings OpenAI's technology to the world. We released ChatGPT; Plugins; DALL·E; and the APIs for GPT-5, embeddings, and fine-tuning. We also operate inference infrastructure at scale. There's a lot more on the immediate horizon. Our customers build fast-growing businesses around our APIs, which power product features that were never before possible. ChatGPT is a prime example of what is currently possible. We simultaneously ensure that our powerful tools are used responsibly. Safe deployment is more important to us than unfettered growth. The Fraud Engineering team works within our Applied Engineering organization identifying and responding to fraudsters on our platform. We are looking for a software engineer with anti fraud & abuse experience to help architect and build our next-generation anti-fraud systems. About the role The Scaled Abuse team protects OpenAI’s products and customers by detecting, preventing, and responding to fraudulent and abusive behavior at scale. We build and operate the backend and data systems that power real-time detection, investigation workflows, and enforcement — balancing strong protections with a great user experience as the platform grows. Our work sits at the intersection of engineering and abuse expertise: we partner closely with Trust & Safety, Security, and Product to understand emerging attack patterns, translate messy signals into clear system behavior, and continuously harden our defenses. The problems are dynamic and ambiguous by default, so we value engineers who can quickly dive into an unfamiliar codebase, develop strong intuition about how it works end-to-end, and propose pragmatic improvements that make the entire stack more resilient. In this role, you will: Design and build systems for fraud detection and remediation while balancing fraud loss, cost of implementation, and customer experience Work closely with finance, security, product, research, and trust & safety ope

About the Team With Codex we’re building an AI software engineer. One that you can pair with, delegate to, or even ask to take on future tasks proactively. Our team is a fast-moving group within OpenAI, bringing together research, engineering, design, and product. We iteratively build the Codex agent harness and product to get the most out of the model, and we iteratively train the model to be great at complex software engineering tasks. The Codex team is responsible for building state-of-the-art AI systems that can write code, reason about software, and act as intelligent agents for developers and non-developers alike. We operate across research, engineering, product, and infrastructure; owning the full lifecycle of experimentation, deployment, and iteration on novel coding capabilities. Codex Enterprise builds the ecosystem, governance, and enterprise capabilities that help Codex spread across developers, teams, and organizations worldwide. The User Activation team owns the product experiences that help developers discover Codex, understand its capabilities, connect it to their workflows, and turn initial usage into sustained adoption across teams. About the Role As Codex adoption grows, our challenge is no longer just building powerful AI capabilities. It is helping developers and teams quickly understand how Codex fits into their work, connect it to the tools and codebases they already use, and unlock workflows that make Codex feel like a true teammate. This role will help build the full-stack product surfaces that drive activation and adoption across Codex Enterprise. You will work across onboarding, workspace setup, integrations, discovery, collaboration, usage insights, and ecosystem capabilities that help Codex spread naturally through organizations. You will partner closely with product, design, research, infrastructure, GTM, and customers to identify where users get stuck, where teams fail to adopt Codex, and what product experiences can turn curiosity int

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 researcher working on Frontier Evals & Environments, you will help build north star model environments to drive progress towards safe AGI/ASI. Your work will directly guide the research programs of the most ambitious training runs happening at OpenAI. Some prior open-sourced evaluations built by researchers in this role include GDPval , SWE-bench Verified , MLE-bench , PaperBench , and SWE-Lancer . If you are interested in feeling firsthand the fast progress of our models, and steering them towards good outcomes, this is the role for you. 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'll: Create ambitious RL environments to push our models to their limits, and measure frontier

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, Connectors, you will teach models how to interface with the top professional software using code. You will help train agents to use code, APIs, tools, and structured integrations to operate across applications like Slack, Google Workspace, GitHub, Notion, Linear, Salesforce, and other core systems of work. You will help enable models to take useful actions across a user’s digital context: finding information, updating systems, coordinating work, generating artifacts, and completing multi-step workflows through the tools teams already use. You will train models to be supercharged by the world’s most important productivity and enterprise software, turning connected tools into a powerful action surface for our agents. 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.

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 researcher working on Frontier Evals & Environments, you will help build north star model environments to drive progress towards safe AGI/ASI. Your work will directly guide the research programs of the most ambitious training runs happening at OpenAI. Some prior open-sourced evaluations built by researchers in this role include GDPval , SWE-bench Verified , MLE-bench , PaperBench , and SWE-Lancer . If you are interested in feeling firsthand the fast progress of our models, and steering them towards good outcomes, this is the role for you. 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 Create ambitious RL environments to push our models to their limits, and measure frontie