Research Engineer/Research Scientist, Personal AGI-Model Experience
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
API
ChatGPT @ 3
Debugging @ 3
Machine 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
The Personal AGI team trains and improves pretrained models for deployment into ChatGPT, the API, and potential future products. The Model Experience team shapes ChatGPT's default character and behavior, including how the model communicates, responds to users, uses its capabilities, and behaves across contexts and languages. The team uses human data, evaluations, reward models, and post-training to improve human-AI interaction.
The work sits at the intersection of research, product, and model design, with close collaboration across OpenAI to conduct research and ensure models are thoughtful, safe, and reliable at scale.
Responsibilities
- Research and develop improvements to machine learning models.
- Own and pursue a research agenda to improve model capability and performance.
- Collaborate closely with research and product teams, including work that allows customers to optimize their own models.
- Build robust evaluations to track modeling improvements.
- Design, implement, test, and debug code across the research stack.
Requirements
- Deep understanding of machine learning and machine learning applications.
- Strong machine learning engineering skills and research experience, especially with novel and highly capable models.
- Good judgment about model behavior and the ability to communicate that judgment effectively.
- Ability to turn ambitious, qualitative problems into concrete training interventions.
- Working knowledge of relevant models and experience building evaluations for model capability improvement.
- Comfort working in and debugging a large machine learning codebase.
- Ability to thrive in a dynamic, technically complex, and collaborative environment.
- Passion for product-driven research and the quality of human-AI interaction.
Benefits
- Base salary of $295,000–$555,000 per year, plus equity.
- Medical, dental, and vision insurance, with employer contributions to Health Savings Accounts.
- Pre-tax accounts for health and dependent care expenses, as well as commuter expenses.
- 401(k) retirement plan with employer match.
- Paid parental, medical, and caregiver leave.
- Paid time off, paid company holidays, office closures, and sick or safe time.
- Mental health and wellness support.
- Employer-paid basic life and disability coverage.
- Annual learning and development stipend.
- Daily office meals and eligible meal delivery credits.
- Relocation support for eligible employees.
- Additional benefits may include charitable donation matching and wellness stipends.
The role is based in San Francisco, California, with a hybrid work model requiring three days in the office per week. OpenAI is an equal opportunity employer and provides reasonable accommodations to applicants with disabilities.