Research Engineer / Research Scientist - Personal AGI, Personality and Model Behavior
Used Tools & Technologies
Not specified
Required Skills & Competences
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.
Machine Learning @ 6
Hiring @ 3
ChatGPT @ 3
AI @ 3
Reinforcement Learning @ 3
- 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 Personality & Model Behavior team within OpenAI’s Personal AGI organization researches how to shape personalities and guide model behavior. The team studies topics such as emotional intelligence, reasoning, and thoughtful model-user interaction, with a focus on understanding how individual users want ChatGPT to behave and creating personalized models integrated into ChatGPT and other OpenAI products.
Responsibilities
- Conduct research on personalization, personality, and model behavior using tools such as synthetic data, reward modeling, and reinforcement learning.
- Build robust evaluations and model training pipelines to support research and development.
- Innovate and develop new post-training methods to improve model behavior and personalization.
Requirements
- Strong machine learning and ML engineering skills, with research experience on novel and highly capable models.
- Experience or knowledge in reinforcement learning and reward modeling.
- Experience with synthetic data and building model evaluations and training pipelines.
- Ability and willingness to dive into large ML codebases to debug issues.
- Comfort working in dynamic, technically complex environments and delivering practical, innovative solutions.
- Product-driven research mindset and experience applying research to deployed products.
Location and Work Model
- This role is based in San Francisco, CA.
- Hybrid work model: 3 days in the office per week.
- Relocation assistance is offered to new employees.
Compensation and Benefits
- Base salary range: $295,000 - $555,000 (base pay may vary by location and individual factors). Total compensation may include equity and performance-related bonuses.
- Benefits include medical, dental, and vision insurance with employer contributions to HSAs; pre-tax accounts for Health FSA, Dependent Care FSA, commuter benefits; 401(k) with employer match; paid parental and medical/caregiver leave; flexible PTO and paid holidays; mental health and wellness support; employer-paid basic life and disability coverage; annual learning & development stipend; daily meals and meal delivery credits; relocation support for eligible employees; and other taxable fringe benefits.
About OpenAI
OpenAI is an AI research and deployment company dedicated to ensuring general-purpose artificial intelligence benefits all of humanity. The company emphasizes safety, diverse perspectives, and inclusive hiring practices. OpenAI is an equal opportunity employer and provides reasonable accommodations for applicants with disabilities.