Research Engineer / Research Scientist, Human Flourishing

About the Team The Human Flourishing team’s mission is to ensure AI systems understand and advance human flourishing. As AI becomes more capable and plays a larger role in people’s lives, we want its human benefits to grow with its capabilities. The Human Flourishing team is part of the broader Personal AGI organization. Our approach has two parts. Firstly, we measure and improve models’ understanding, capability, and propensity to act according to people’s values and to help them achieve their long-term goals. Secondly, we directly scale tangible impact for users in human domains like education and mental health, working across research, product, and partnerships to increase the benefits over a billion people experience weekly when they use ChatGPT. Our recent work includes Beneficial RL https://alignment.openai.com/beneficial-rl/, which investigates how training for beneficial behavior generalizes across settings, and MentalHealthBench https://openai.com/index/introducing-mentalhealthbench/, a benchmark developed with mental health experts to evaluate realistic conversations. About the Role We’re looking for an exceptional, hands-on researcher to turn difficult-to-define signals of long-term flourishing into measurable improvements in model behavior. You’ll help set research direction, build what is needed to test your ideas, and drive successful work into the models and products we ship. We’re especially interested in researchers with deep experience improving frontier models through pretraining or reinforcement learning (RL) / post-training, especially on less verifiable problems, or researchers who combine strong LLM skills with deep expertise in domains like education or mental health. Prior experience in these domains is not required. In this role, you will - Develop scalable training methods across the training stack that improve how models understand people’s values, support their agency, and help them achieve long-term goals. - Lead high-leverage research from an open question to a shipped improvement: choose a hard-to-define problem, iteratively define success, run experiments, and integrate into frontier models. - Build RL environments for difficult-to-verify outcomes, and study whether beneficial behavior generalizes across settings. - Create evaluations grounded in human expertise and feedback that reveal capability gaps, unintended incentives in RL, and failures that aggregate scores can miss. - Test whether measures of model behavior predict better learning, wellbeing, and other long-term outcomes, and use those findings to guide training. - Build new 0→1 capabilities in human domains that may have an increasing impact with upcoming increases in model intelligence and test-time compute. - Partner with product teams, engineers, partnerships teams, and domain experts to deploy promising methods, measure their effects in real use, and turn what you learn into further improvements. - Assess AI’s impacts on human flourishing at the scale of over a billion users. You might thrive in this role if you - Care deeply about helping AI improve people’s lives, and feel this is a responsibility that comes with increasingly capable models. - Have an unusually strong research record in pretraining or RL / post-training research, especially in a hard-to-verify area; or combine strong LLM research skills with deep expertise in education, mental health, or a related field of human benefit. - Are a hands-on builder who can turn ideas into rigorous experiments, write and debug code, and work directly with data and training infrastructure. - Have the taste to choose consequential problems and actionable steps on the path to solving those problems. - Take ownership of ambiguous problems and choose methods based on the impact they can deliver, including when the most useful work is unglamorous. - Care about whether a capability will scale, generalize, and make it into the real world—not just whether it can be shown in a paper or prototype. - Work well across disciplines and can grok the most important bottlenecks to scaling our impact in a multidisciplinary problem. If you’re excited about ensuring AI systems advance human flourishing, we’d love to hear from you. 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. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upo