Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 3
ChatGPT @ 3
LLM @ 6
Reinforcement Learning @ 6
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
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, the team aims for human benefits to grow alongside those capabilities. The Human Flourishing team is part of the broader Personal AGI organization.
The team’s approach has two parts:
- Measure and improve models’ understanding, capability, and propensity to act according to people’s values and help them achieve their long-term goals.
- Scale tangible impact for users in human domains such as education and mental health by working across research, product, and partnerships to increase the benefits experienced by ChatGPT users.
Recent work includes Beneficial RL, which investigates how training for beneficial behavior generalizes across settings, and MentalHealthBench, a benchmark developed with mental health experts to evaluate realistic conversations.
About the Role
The team is seeking an exceptional, hands-on researcher to turn difficult-to-define signals of long-term flourishing into measurable improvements in model behavior. The role involves setting research direction, building the tools needed to test ideas, and driving successful work into shipped models and products.
The team is especially interested in researchers with deep experience improving frontier models through pretraining or reinforcement learning (RL) and post-training, particularly on less verifiable problems. Researchers who combine strong LLM skills with deep expertise in domains such as education or mental health are also encouraged to apply. Prior experience in these domains is not required.
Responsibilities
- 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 by choosing difficult-to-define problems, iteratively defining success, running experiments, and integrating results 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 to reveal capability gaps, unintended incentives in RL, and failures that aggregate scores may miss.
- Test whether measures of model behavior predict better learning, wellbeing, and other long-term outcomes, and use the findings to guide training.
- Build new 0→1 capabilities in human domains that may have increasing impact as model intelligence and test-time compute improve.
- Partner with product teams, engineers, partnerships teams, and domain experts to deploy promising methods, measure their effects in real-world use, and turn findings into further improvements.
- Assess AI’s impacts on human flourishing at the scale of more than a billion users.
Requirements
- A strong research record in pretraining or RL/post-training research, especially in a hard-to-verify area; or strong LLM research skills combined with deep expertise in education, mental health, or a related field of human benefit.
- Ability to turn ideas into rigorous experiments, write and debug code, and work directly with data and training infrastructure.
- Ability to choose consequential problems and actionable steps toward solving them.
- Ownership of ambiguous problems and the ability to choose methods based on the impact they can deliver.
- Focus on whether capabilities can scale, generalize, and reach the real world, rather than only being demonstrated in a paper or prototype.
- Ability to work across disciplines and understand the key bottlenecks to scaling impact in a multidisciplinary problem.
- Commitment to helping AI improve people’s lives and ensuring that increasingly capable AI systems advance human flourishing.
About OpenAI
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. The company develops AI systems and seeks to safely deploy them through its products.
OpenAI is an equal opportunity employer and does 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 characteristics. Background checks are administered in accordance with applicable law. OpenAI is committed to providing reasonable accommodations to applicants with disabilities.
Benefits
- Medical, dental, and vision insurance for employees and their families, with employer contributions to Health Savings Accounts.
- Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses.
- 401(k) retirement plan with employer match.
- Paid parental leave, medical leave, and caregiver leave.
- Paid time off, paid company holidays, office closures, and paid sick or safe time as required by applicable law.
- Mental health and wellness support.
- Employer-paid basic life and disability coverage.
- Annual learning and development stipend.
- Daily meals in offices and meal delivery credits where eligible.
- Relocation support for eligible employees.
- Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may be provided.
The base pay offered may vary based on market location, job-related knowledge, skills, and experience. Total compensation also includes equity and performance-related bonuses for eligible employees.