Description
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 position is $295K – $555K, and total compensation also includes generous equity, performance-related bonuses for eligible employees, and the following benefits.
Benefits include:
- 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
- Additional taxable fringe benefits, such as charitable donation matching and wellness stipends
About the Team
The Personalization-Memory team, within OpenAI's broader Personal AGI organization, focuses on developing agents that can learn from prior interactions to become more helpful and efficient over time. They build general-purpose memory and personalization capabilities that transfer across ChatGPT and other agentic products, collaborating with applied engineering on product surfaces that allow users to interact with memory.
About the Role
As a Research Engineer / Research Scientist on the Personalization-Memory team, you will research and develop improvements to memory usage and personalization in OpenAI's frontier models. The team works on reinforcement learning, dataset creation, evaluations, and other post-training methods, partnering closely with research and product teams across the company to realize the vision of a truly personalized ChatGPT.
Responsibilities
- Own and pursue a research agenda for improving memory use and personalization in frontier models.
- Build robust evaluations for tracking modeling improvements.
- Design, implement, test, and debug code across the research stack.
- Collaborate closely with research and product teams to influence the shape of technical solutions in the product.
Requirements
- Passionate about personalization and building personalized assistants.
- Experience working with user signals and human data to turn feedback into reliable signals for training and evaluation.
- Deep understanding of frontier model post-training and machine learning applications.
- Principled approaches and research craftsmanship.
- Comfortable diving into a large ML codebase to debug.
- Thrives in a fast-paced, dynamic, and technically complex environment.