Description
We are seeking a Research Engineer / Research Scientist to join our Proactivity Research team within OpenAI's broader Personal AGI team. The successful candidate will research and develop improvements to our models' personalization and agentic capabilities.
Compensation The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. The salary range for this role is $295K – $555K, with generous equity, performance-related bonuses, 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
- 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
About the Team The Proactivity Research team is focused on making our models in ChatGPT and future potential products proactive in ways that are truly useful. We're laying the technical foundations for AI that can anticipate what users need in real time, adapt as their goals and preferences shift, and build a deeper, evolving understanding of the person it's helping.
About the Role As a Research Engineer / Scientist, you will research and develop improvements to our models' personalization and agentic capabilities. Our team works on reinforcement learning, dataset creation, evaluations, and other post-training methods. You will partner closely with research and product teams across the company to realize the vision of a highly personalized, collaborative, and proactive assistant.
Responsibilities
- Own and pursue a research agenda to improve the proactivity and ability of our models to further user goals
- Build robust evaluations for tracking modeling improvements
- Design, implement, test, and debug code across our research stack
- Collaborate closely with the other research and product teams to influence the shape of technical solutions in the product
Requirements
- Have a deep understanding of machine learning and machine learning applications
- Have a working knowledge of LLM post-training and evaluation approaches
- Are passionate about, or have experience thinking about, personalization and enabling users to achieve their goals
- Are comfortable diving into a large ML codebase to debug
- Thrive in a dynamic and technically complex environment