Job Posting Researcher, Synthetic RL Location San Francisco Employment Type Full time Department Research Compensation $295K – $445K • Offers Equity The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits. Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit) 401(k) retirement plan with employer match Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks) Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law) Mental health and wellness support Employer-paid basic life and disability coverage Annual learning and development stipend to fuel your professional growth Daily meals in our offices, and meal delivery credits as eligible Relocation support for eligible employees Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided. More details about our benefits are available to candidates during the hiring process. This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions. About the Team The Synthetic RL team develops reinforcement learning methods that leverage synthetic data, environments, and feedback to train and evaluate frontier AI models. The team explores approaches such as self-play, simulators, and other synthetic evaluations to push model capability, generalization, and alignment beyond what is possible with the current prevailing methodology. About the Role As a Research Scientist on the Synthetic RL team, you will develop novel reinforcement learning techniques that use synthetic environments and feedback to improve large-scale models. You’ll work closely with other researchers to design experiments, analyze learning dynamics, and translate research insights into training approaches used in production systems. We’re looking for researchers who enjoy working on open-ended problems, value fast iteration, and want their work to directly shape how frontier models are trained. 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: Research and develop reinforcement learning algorithms Design and run experiments to study training dynamics and model behavior at scale Collaborate with engineers and researchers to integrate successful approaches into model training pipelines You might thrive in this role if you: Have a strong background in reinforcement learning, machine learning research, or related fields Have strong engineering and statistical analysis skills Enjoy exploring new problem spaces where data, objectives, and evaluation are imperfect or evolving Are motivated by seeing research ideas influence real-world AI systems About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.