Researcher, Multimodal Safety

About the Team Safety Systems manages the complete lifecycle of safety efforts for OpenAI’s frontier models, ensuring our models are deployed responsibly and have a positive impact on society. Our work spans diverse research and engineering initiatives—from system-level safeguards and model training to evaluation and red-teaming—all aimed at mitigating misuse, misalignment, and maintaining our high bar for safety. We lead OpenAI's commitment to developing and deploying safe Artificial General Intelligence (AGI), fostering a culture of trust, responsibility, and transparency. Our goal is to continuously learn from deployments, distribute AI’s benefits widely, and ensure that powerful tools remain aligned with human values and safety considerations. About the Role We are hiring a Product Manager to focus on risk related to multimodal models. In this role, you will drive initiatives which ensure that OpenAI’s audio, image, and video deployments are safe, impactful, and aligned with user needs and technical innovation. You will clarify strategic priorities, develop safety-focused product roadmaps, and collaborate closely with AI researchers, software engineers, policy experts, and cross-functional partners. This role suits a proactive, technically skilled product manager adept at adversarial thinking and excited to tackle challenging, ambiguous problems through structured analysis and collaborative decision-making. This position is based in San Francisco, CA, with relocation assistance available. In this role, you will: Partner closely with AI research, engineering, data science, policy teams, and other stakeholders to embed safety throughout the development and deployment of multimodal AI models - such as GPT-Live and ChatGPT Images - as well as multimodal capabilities in frontier AI models. Develop comprehensive frameworks for understanding and mitigating deployment safety risks, drawing on data analysis, expert consultation, and adversarial assessments. Define strate

About the Team Safety Systems manages the complete lifecycle of safety efforts for OpenAI’s frontier models, ensuring our models are deployed responsibly and have a positive impact on society. Our work spans diverse research and engineering initiatives—from system-level safeguards and model training to evaluation and red-teaming—all aimed at mitigating misuse, misalignment, and maintaining our high bar for safety. We lead OpenAI's commitment to developing and deploying safe Artificial General Intelligence (AGI), fostering a culture of trust, responsibility, and transparency. Our goal is to continuously learn from deployments, distribute AI’s benefits widely, and ensure that powerful tools remain aligned with human values and safety considerations. Within Safety Systems, the Model Policy team works to ensure that frontier models behave safely and reliably in real-world environments by designing policies that define safe model behavior. Our relevant publications include: Safety at every step OpenAI GPT6 System Card OpenAI Model Spec GPT-Live ChatGPT Images 2.5 About the Role We are hiring a Model Policy Manager to focus on the safety of multimodal models. In this role, you will shape how OpenAI identifies, evaluates, and addresses risks in multimodal AI models - such as GPT-Live and ChatGPT Images - as well as multimodal capabilities in frontier AI models. 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: Design and maintain model policies for audio, image, video, and omni-modal behavior. Translate theories of harm and threat models into behavioral safety policies, evaluation criteria, grading guidance, and safeguards. Identify and analyze safety regressions and failure patterns to identify gaps in existing policies and inform policy iteration. Develop policy artifacts that support model training, evaluation, and deployment, including behavior i

About the Team The Safety Systems team is at the forefront of OpenAI's mission to build and deploy safe AGI, driving our commitment to AI safety and fostering a culture of trust and transparency. The Model Policy team aligns model behavior with desired human values and norms. We co-design policy with models and for models by driving rapid policy taxonomy iteration based on data and defining evaluation criteria for foundational models’ ability to reason about safety. Key focus areas include: catastrophic risk, mental health, teen safety and multimodal safety. About the Role Providing access to frontier AI systems raises complex questions around dual-use science and catastrophic risk. How should models respond to requests involving chemical synthesis, biological experimentation, or pathogen research? Where is the boundary between legitimate scientific inquiry and information that could enable misuse? How do we design policies that meaningfully reduce risk without unnecessarily restricting beneficial research? This is a senior role in which you’ll help shape policy creation and development at OpenAI for addressing biological and chemical risks. You will develop structured policy frameworks and taxonomies to guide safe model behavior. This role sits at the intersection of biosecurity expertise, AI safety research, and policy design. You will help ensure that frontier AI systems can support beneficial life sciences research, such as drug discovery, public health, and biosafety, while reducing the risk that these capabilities could be misused. 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’ll: Design and maintain model policies governing chemical and biological risk, defining how models should safely handle dual-use scenarios. Develop structured taxonomies of chemical and biological risk that inform model training data, evaluation benchmarks, and safet

About the Team Our Safety Systems team is at the forefront of OpenAI's mission to build and deploy safe AGI, driving our commitment to AI safety and fostering a culture of trust and transparency. The Model Policy team aligns model behavior with desired human values and norms. We co-design policy with models and for models by driving rapid policy taxonomy iteration based on data and defining evaluation criteria for foundational models’ ability to reason about safety. Key focus areas include: catastrophic risk, mental health, teen safety and multimodal safety. About the Role Providing access to frontier AI systems raises complex questions around dual-use science and catastrophic risk. How should models respond to requests involving chemical synthesis, biological experimentation, or pathogen research? Where is the boundary between legitimate scientific inquiry and information that could enable misuse? How do we design policies that meaningfully reduce risk without unnecessarily restricting beneficial research? This is a senior role in which you’ll help shape policy creation and development at OpenAI for addressing biological and chemical risks. You will develop structured policy frameworks and taxonomies to guide safe model behavior. This role sits at the intersection of biosecurity expertise, AI safety research, and policy design. You will help ensure that frontier AI systems can support beneficial life sciences research, such as drug discovery, public health, and biosafety, while reducing the risk that these capabilities could be misused. Our relevant publications: Preparedness framework Preparing for future AI capabilities in biology Safety evaluations hub OpenAI GPT5 System Card Evaluating Fairness in ChatGPT Improving Model Safety Behavior with Rule-Based Rewards OpenAI Model Spec Your Responsibilities: Design and maintain model policies governing chemical and biological risk, defining how models should safely handle dual-use scenarios. Develop structured taxonomi

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

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 Multimodal team works across voice, image generation, and other multimodal experiences to turn frontier research capabilities into reliable products. The team connects product usage and failure patterns with research, evaluation, data, inference, capacity, and external partnerships so that model and product improvements translate into better experiences for users. About the Role We are seeking a Technical Program Manager to build the flywheel that helps ChatGPT multimodal products learn from real-world usage and improve quickly. You will lead programs spanning production-signal mining, evaluation and data pipelines, research-to-production parity, multimodal capacity planning, and complex cross-functional dependencies for voice and image-generation launches. You will work closely with product engineering, research, Human Data, inference and capacity teams, safety partners, and external vendors or product partners. Success requires technical depth, strong systems thinking, comfort with ambiguity, and the ability to turn fragmented or manual work into durable mechanisms that teams adopt. 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: Build a system for mining production conversations and product signals to identify representative multimodal workflows, user needs, and failure modes. Establish and maintain evaluations for the highest-priority multimodal behaviors and use cases, with clear coverage, quality standards, and ownership. Package production signals into decision-ready data and