Signal Integrity Engineer in United States

About the Team The CoT Monitorability team at OpenAI studies whether and when the chain-of-thought of frontier reasoning models is monitorable enough to support scalable oversight. We study how to measure monitorability , which training mechanisms affect monitorability, and speculative methods to improve monitorability. While we mostly focus on CoT monitorability at the moment, we care more generally about any form of monitorability, auditing methods, and improving alignment. We were the first to show that chain-of-thought monitoring can be a practical additional safety mechanism, and today our monitoring systems are actively used on OpenAI’s largest RL training runs to detect misbehavior. The issues we surface are then used to help improve our reward functions, environments, etc (without directly training against a CoT monitor). Our work sits in Alignment and intersects with model training, alignment evaluations, monitoring, and frontier-risk research.We care most about monitorability where the stakes are high, and about preserving useful oversight signals as models become more capable. About the Role We’re looking for a researcher with strong empirical ML expertise and a deep interest in model behavior, alignment, or interpretability. Direct chain-of-thought interpretability experience is welcome but not required; strong candidates may come from broader interpretability, alignment, model training, or investigative model-behavior work. As a researcher on the Alignment team, you will design and run experiments that improve our understanding of model monitorability. You will investigate how training interventions across the model-development pipeline influence whether reasoning remains legible, build evaluations that make those questions measurable, and help translate findings into practical oversight and training recommendations. You may also help develop new monitoring models or methods and apply them to OpenAI’s largest training runs. This role is especially well

About the Team The Ads Support Delivery team is responsible for helping successfully operate and grow on our Ads product. This includes technical guidance, troubleshooting complex delivery and monetization issues, and partnering closely with Product, Engineering, Trust & Safety and Go-To-Market teams to resolve customer-impacting problems and improve the platform over time. The team’s mission is to deliver a high-quality customer experience at scale by combining strong human support with automation, self-service, and AI-enabled workflows, while maintaining high operational rigor. About the Role: As a Support Delivery Lead for Ads, you will lead a team responsible for end-to-end support delivery across the ads ecosystem, including campaign setup, delivery, billing, measurement, and policy navigation. You will set the operational bar for quality, responsiveness, and consistency; coach and grow the team; and translate support signals into actionable improvements with Engineering, Product, and Go-To-Market partners. 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 and support a team of Ads support engineers, ensuring they have the tools, clarity, and coaching needed to operate at a high bar in a technically complex domain. Set clear expectations and operating standards, run recurring performance reviews, and build development plans that grow both technical depth (ad tech fluency) and customer-facing excellence. Design and continuously improve support coverage for ad buyers, ensuring the team can diagnose delivery issues and monetization and integration issues with equal rigor. Act as the bridge between Support Delivery, Engineering, Product, and Go-To-Market teams. Drive alignment on priorities, escalation paths, launch readiness, tooling improvements and mechanisms to reduce repeated customer pain points. Partner with engineering teams

About the Team The Monetization team is a cross-functional group working across engineering, product, research, and design to build the foundational systems that will help OpenAI scale access to intelligence responsibly. Our mission is to develop user-first, privacy-preserving monetization products, including next-generation ads experiences that strengthen user trust, unlock economic opportunity, and support OpenAI’s long-term innovation. Monetization plays a critical role in enabling OpenAI to continue pushing the boundaries of AI capabilities while ensuring the benefits of AGI are broadly shared. We believe monetization must be aligned with user value, uphold rigorous privacy and safety standards, and sustain a healthy ecosystem of developers and businesses. This team operates in a greenfield environment and moves quickly through prototyping, experimentation, and iterative deployment. We partner closely with Product, Design, and Research to bring research breakthroughs into real-world systems at global scale. About the Role We’re looking for an experienced Software Engineer to build measurement systems that connect ad interactions to meaningful advertiser outcomes while protecting user privacy. In this foundational role, you’ll design infrastructure for conversion signals, attribution, reporting, and feedback loops across OpenAI’s ads products. This role is ideal for engineers who have built large-scale ads measurement, data, experimentation, marketplace, or distributed systems and want to apply that experience in a highly ambiguous 0→1 environment. You’ll work across event collection and normalization, deduplication and matching, attribution and modeled measurement, privacy-safe aggregation, reporting, and high-quality labels for ads optimization. We are hiring engineers who can independently own complex systems, make sound technical tradeoffs, and help define what should be built. You’ll work closely with Ads Delivery, Ads ML, Product, Research, Privacy, Data Sc

About the Team OpenAI’s mission is to ensure that general-purpose artificial intelligence benefits all of humanity. Our Communications team supports OpenAI’s mission and goals by clearly and authentically explaining our technology, values, and approach to safely building powerful AI. The Internal Communications team aims to create clarity, trust, and shared understanding that inspires our employees to do their best work. About the Role We are looking for an Internal Communications professional to support our Enterprise and & Growth portfolio, specifically B2B, Revenue, Partnerships, Marketing, Enterprise Engineering, Ads, and Commerce teams. This role is well suited for a highly organized communicator who writes clearly, learns quickly, brings calm execution to a fast-moving environment, and enjoys finding creative ways to keep employees informed and connected. In this role, you will: Support day-to-day internal communications for the Enterprise & Growth portfolio, including product, partnership, leadership, and organizational announcements. Help plan and execute internal events for supported executives and teams, including org-wide All Hands, managers meetings, Q&As, leadership AMAs, employee engagement moments, and launch-related gatherings. Support logistics and execution for company-wide customer storytelling programs, bringing customer insights, examples, and impact stories to employees. Monitor high-traffic Slack channels and other employee feedback signals across supported teams to identify emerging questions, information gaps, and opportunities to improve clarity or connection. Maintain intake and calendar, tracking key moments, milestones, dependencies, audiences, and review timelines. Contribute to broader Internal Communications priorities as needed, bringing flexibility, curiosity, and strong follow-through across the team. You might thrive in this role if you have: 3+ years of experience in internal communications, event coordination, market

About the Team The Intelligence and Investigations team seeks to rapidly identify and mitigate abuse and strategic risks to ensure a safe online ecosystem. We are dedicated to identifying emerging abuse trends, analyzing risks, and working with our internal and external partners to implement effective mitigation strategies to protect against misuse. Our efforts contribute to OpenAI's overarching goal of developing AI that benefits humanity. The Strategic Intelligence & Analysis (SIA) team provides safety intelligence for OpenAI’s products by monitoring, analyzing, and forecasting real-world abuse, geopolitical risks, and strategic threats. Our work informs safety mitigations, product decisions, and partnerships, ensuring OpenAI’s tools are deployed securely and responsibly across critical sectors. About the Role As a Quantitative Intelligence Analyst , you will focus on discovering novel and emerging risks in complex human–AI systems before they are well-defined, measurable, or widely understood. You will use deep subject matter expertise and quantitative tooling to surface weak, early, and unconventional risk signals. You will build analytic models that explain how harms could emerge and translate ambiguous patterns into structured, data-driven insight. Your work will help identify potential gaps in policy or coverage and operationalize previously unmeasured problems into signals that can support detection, mitigation, and planning downstream. You will develop analytical frameworks that map how new risks form, evolve, and propagate as products change, policies shift, and external events unfold. Your analyses will directly inform strategic risk prioritization and planning across the company, with regular visibility through strategic risk products. This role is based in office (hybrid, 3 days/week). Relocation support is available In this role, you will: Discover and define new quantitative risk signals where no established metrics exist, using subject matter exp

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 The Personal AGI team seeks to empower all of humanity to benefit from frontier intelligence in whatever way they choose. We are responsible for training models to deploy to millions of users globally via ChatGPT, the API, and future products. We aim to evolve ChatGPT from a chatbot to an infinitely capable and personalized superassistant supporting human flourishing. We work on defining, measuring, and improving capabilities across the training stack. Our focus areas include but are not limited to model behavior, personalization, safety, factuality, instruction following, personality, interactivity, multilingual fluency, world interaction, and bringing agents to everyone. We chart the course for what to strive towards. We partner closely with research and product teams across the company ensuring that our models are safe, efficient, and reliable. About the Role You’ll work as a Research Engineer / Scientist on the North Stars team within the broader Personal AGI research org. You will work on bringing the next generation of AI-enabled experiences to all of humanity by closing the capability overhang between power users and the average consumer, including areas like tool-use, feature discovery, connectors, and instruction following. You will think deeply about the current bottlenecks in model behavior, translate these insights into robust evals, training data, reward signals, and model and harness improvements. We're looking for individuals with strong ML engineering skills and research experience passionate about creative, product-driven research. 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 to improve model capability and performance. Collaborate closely with the other research and product teams, allowing customers to optimize their own models. Build robust evaluations for tracking modelin

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, you will research and develop improvements to memory usage and personalization in OpenAI's frontier models. Our team works on reinforcement learning, dataset creation, evaluations, and other post-training methods. We partner closely with research and product teams across the company to realize the vision of a truly personalized ChatGPT. We're looking for individuals who have a background in frontier model post-training, are able to iterate quickly, and who are passionate about product-driven research. 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 memory use 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: Are passionate about personalization and building personalized assistants. Have experience working with user signals and human data to turn feedback into reliable signals for training and evaluation. Have a deep understanding of frontier model post-training and machine learning applications. Value principled approaches and research craftsmanship. Are comfortable diving into a lar

About the Team The Intelligence and Investigations team seeks to rapidly identify and mitigate abuse and strategic risks to ensure a safe online ecosystem. We are dedicated to identifying emerging abuse trends, analyzing risks, and working with our internal and external partners to implement effective mitigation strategies to protect against misuse. Our efforts contribute to OpenAI's overarching goal of developing AI that benefits humanity. The Strategic Intelligence & Analysis (SIA) team provides safety intelligence for OpenAI’s products by monitoring, analyzing, and forecasting real-world abuse, geopolitical risks, and strategic threats. Our work informs safety mitigations, product decisions, and partnerships, ensuring OpenAI’s tools are deployed securely and responsibly across critical sectors. About the Role As an Agentic Risk Analyst, you will shape OpenAI’s operating picture for current agentic risk across products and platforms. You will bring a strategic, system-level perspective to current risks, connecting individual incidents, technical findings, abuse patterns, and external developments to relevant workstreams, mitigations, owners, dependencies, and residual gaps. You will analyze how risks emerge through autonomy, multi-step task execution, tool use, memory, retrieval, connectors, computer-use capabilities, and multi-agent workflows, with a particular focus on both adversarial misuse and unintended system behavior. By synthesizing signals from investigations, evaluations, red teaming, security reviews, product launches, external research, and real-world incidents, you will maintain a current view of material risks and evolving threat patterns. Your work will help turn complex and often ambiguous signals into coordinated decisions and measurable follow-through across product, safety, security, policy, and governance teams. You will work closely with investigators, engineers, product, policy, safety, and security teams, and measurement and forecasting

About the Team OpenAI’s mission is to build safe artificial general intelligence (AGI) that benefits all of humanity. Achieving this requires bringing the world’s most exceptional talent under one roof to push the boundaries of what’s possible. Our Research Recruiting team plays a critical role in this effort. We are an embedded part of the research organization—working side by side with our research staff to deeply understand evolving priorities, build trust, and strategically shape the future of OpenAI’s talent. About the Role We are looking for a highly strategic recruiter to work closely with the Head of Research Recruiting on a small set of unusually important, high-touch searches and candidate relationships. This role will focus on exceptional talent who does not move through a standard recruiting process: highly visible researchers, technical leaders, operators, and other special-interest candidates where timing, discretion, market intelligence, and tailored engagement matter as much as process execution. This is not a conventional req-based recruiting role. You will help identify where the market is moving, develop intelligence on top talent and competitor activity, translate that intelligence into action, and orchestrate bespoke recruiting strategies for candidates who require a more nuanced path into OpenAI. You should be able to translate these signals and states into clear, actionable advice for leaders and then make it happen. In this role, you will: Partner directly with the Head of Research Recruiting and research leadership team to define priority talent targets and shape bespoke engagement strategies. Build and maintain deep market intelligence across frontier AI, research, engineering, and adjacent talent ecosystems, including competitor movement, candidate motivations, and relationship context. Proactively identify, map, and cultivate exceptional high-profile talent before there is a formal or standard hiring process attached. Translate weak signa

About the Team Codex is OpenAI’s first-party developer product focused on agentic software engineering. We’re building tools that help engineers design, write, test, and ship code faster—safely and at scale. We partner tightly with research and product to translate model advances into tangible developer productivity. About the Role As a Data Scientist on Codex, you will measure and accelerate product-market fit for AI developer tools. You’ll define what “developer productivity” means for our product, run experiments on new coding models and UX, and pinpoint where the model helps or hurts across languages and tasks. Your insights will directly shape how an entire industry builds software. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will Embed with the Codex product team to discover opportunities that improve developer outcomes and growth Design and interpret A/B tests and staged rollouts of new coding models and product features Define and operationalize metrics such as suggestion acceptance, edit distance, compile/test pass rates, task completion, latency, and session productivity Build dashboards and analyses that help the team self-serve answers to product questions (by language, framework, repo size, task type) Diagnose failure modes and partner with Research on targeted improvements (model quality signals, user feedback, evals) You might thrive in this role if you have 5+ years in a quantitative role at a developer-facing or high-growth product Fluency in SQL and Python; comfort with experiment design and causal inference Experience defining product metrics tied to user value Ability to communicate clearly with PM, Eng, and Design—and to influence product direction You could be an especially great fit if you have Strong programming background; ability to prototype, run simulations, and reason about code quality Familiarity with IDE/extensi

About the team OpenAI’s Enterprise Go-To-Market organization helps the world’s largest companies adopt and scale our AI platform across their business—from ChatGPT Enterprise to our developer platform and APIs. We partner with organizations across Financial Services, Life Sciences, and Retail to build new AI-powered customer experiences, transform operations, and reimagine how work gets done in highly regulated and technically complex environments. As adoption accelerates through pilots, experimentation, and developer-led use cases, the GTM team turns that momentum into durable, enterprise-wide deployments. Sales Development sits at the front of this motion—where technical curiosity becomes executive engagement and OpenAI’s enterprise relationships begin. About the role We are hiring a Sales Development Manager, AMER to lead a team of SDRs supporting our Large Enterprise business across North America. Reporting into Sales Development leadership, this role will be responsible for coaching and developing a high-performing team focused on generating qualified pipeline and creating strategic enterprise opportunities. This is a foundational front-line leadership role within OpenAI’s enterprise GTM organization. You will help define how we engage prospective customers, convert product and developer interest into enterprise conversations, and scale repeatable outbound and inbound motions across some of the world’s largest organizations. You will partner closely with Sales, Marketing, Solutions Engineering, Partnerships, and Strategy & Operations to drive pipeline generation and help shape the future of OpenAI’s enterprise growth engine. In this role, you will: Lead, coach, and develop a team of SDRs supporting Large Enterprise, Verticals, and Strategic Accounts across AMER Drive high-quality pipeline generation through outbound prospecting, inbound qualification, account-based motions, and product-led signals Establish strong operational rigor around activity metrics,

About the team The Intelligence and Investigations team seeks to rapidly identify and mitigate abuse and strategic risks to ensure a safe online ecosystem in close collaboration with our internal and external partners. Our efforts contribute to OpenAI's overarching goal of developing AI that benefits humanity. This role focuses specifically on AI Safety: understanding and mitigating risks created or amplified by increasingly capable AI systems. It is not a cybersecurity, information security, or corporate security role. The Strategic Intelligence & Analysis (SIA) team provides safety intelligence for OpenAI’s products by monitoring, analyzing, and forecasting real-world abuse, geopolitical risks, and strategic threats. Our work informs AI safety mitigations, product decisions, and partnerships, ensuring OpenAI’s tools are deployed responsibly across critical sectors. About the role We are looking for a Frontier AI Risks Lead to help us understand potential harms and misuse of AI in a time of rapid, sustained change. We seek to understand how developments in AI could intersect with misuse and abuse, accelerating existing harm areas and creating novel risks. We seek to scan available signals and use strategic foresight methodologies to enable proactive detection and mitigation of frontier AI risks. This is an AI safety role focused on frontier and systemic risks, including model misalignment, recursive self-improvement (RSI), multi-agent interaction, loss of control, runaway agents, and related emerging failure modes. In this role, you will help provide a strategic-level perspective on a range of frontier AI safety areas, producing actionable understanding of issues relevant to OpenAI’s platforms, systems, and broader mission. Utilizing mixed quantitative and qualitative methodologies, you will spot early warning signs, pull threads on potentially concerning behavior, and turn weak signals into clear, prioritized risk calls. You will focus on upstream ecosystem sc

About the Team OpenAI’s mission is to build safe artificial general intelligence (AGI) that benefits all of humanity. Achieving this requires bringing the world’s most exceptional talent under one roof to push the boundaries of what’s possible. Our Research Recruiting team plays a critical role in this effort. We are an embedded part of the research organization, working side by side with our research staff to deeply understand evolving priorities, build trust, and strategically shape the future of OpenAI’s talent. About the Role You will own and execute long-term talent strategies to identify, engage, and recruit many of the world’s leading and emerging AI researchers, research engineers, and technical scientists working at the frontier of machine learning. This is not a traditional execution-focused recruiting role. You will operate as a strategic partner to OpenAI’s research staff, helping define hiring priorities, shape search strategy, influence candidate evaluation, and guide hiring decisions that directly impact the direction and quality of our frontier-model research and fulfillment of our mission. In this role, you will: Partner directly with research and technical staff to define hiring priorities, shape search strategies, and anticipate future talent needs as technical roadmaps evolve. Proactively identify and cultivate exceptional AI/ML research talent across industry, academia, and emerging labs, often before formal hiring needs exist. Use market insights and candidate signals to influence hiring decisions, leveling, and compensation strategy for highly specialized research roles. Serve as a trusted advisor throughout candidate evaluation and closing — helping leaders calibrate for research excellence, long-term potential, and organizational fit. Collaborate closely with your sourcing partner to execute complex, high-impact searches in ambiguous or rapidly evolving technical domains. You might thrive in this role if you: Significant experience recruitin

About the Team The Future of Computing Research team is an applied research team within the Consumer Devices group focused on developing new methods, models, and evaluation frameworks that support our vision for the future of computing. We work at the frontier of multimodal AI, helping turn emerging model capabilities into product experiences that are useful, delightful, and worthy of long-term trust. Our work explores a new class of AI systems that can learn over time, adapt to individuals, and support people in the flow of daily life. This includes long-term memory, user modeling, and personalization systems that are aligned not just with immediate satisfaction, but with a person’s broader goals, values, and well-being. We work closely across research, engineering, design, product, and safety to define what it means to build AI systems that know you over time, act at the right moment, and help in ways that are context-aware, respectful, and demonstrably beneficial. About the Role We are looking for a Research Engineer / Scientist to join the Future of Computing Research team to work on RLHF and post-training for personalized, multimodal AI systems. This role will focus on building the learning and evaluation foundations that help models become more context-aware, adaptive, and useful over time. You will work on problems such as reward modeling, preference learning, long-horizon evaluation, and policy improvement for systems that must make high-quality behavioral decisions in realistic user settings. The work is deeply product-grounded: success is not just higher benchmark performance, but better model behavior in real-world use. The ideal candidate is excited about pushing beyond one-turn assistant behavior toward systems that improve through feedback, learn from richer signals, and are trained against meaningful notions of user value. Internally, that maps closely to the need for careful reward design, feedback loops, and evaluation frameworks that test whether i