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The Personalization-Memory team, within OpenAI's broader Personal AGI organization, is focused on developing agents that can learn from prior interactions in order to become more helpful and efficient over time. We build general-purpose memory and personalization capabilities that transfer across ChatGPT and other agentic products, and we collaborate with applied engineering on the product surfaces that allow users to interact with memory.
About the Role
As a Research Engineer / Research Scientist on the Personalization-Memory team, your work will span memory architecture, post-training, and developing long-horizon tasks for training and evaluations.
We're looking for individuals who have a background in reinforcement learning research, are able to iterate quickly, and who can convert scientific rigor and long-term research into realized product impact.
This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.
In this role, you will:
Own and pursue a research agenda for improving long-horizon memory and personalization in frontier models.
Build robust evaluations for tracking modeling improvements.
Design, implement, test, and debug code across our research stack.
Collaborate closely with the research and product teams to influence the shape of technical solutions in the product.
Love being on the cutting edge of RL and frontier model research.
Value principled approaches and research craftsmanship.
Are passionate about long-horizon tasks, memory, and turning your research into product impact.
Are comfortable diving into a large ML codebase to debug.
Thrive in a fast-paced, dynamic, and technically complex environment.
Fast-track your ML job hunt :