Reinforcement Learning Researcher Technology Posted

Position: Reinforcement Learning Researcher Technology company   $200k to $350k USD base a year Posted today
# Reinforcement Learning Researcher Technology company
* Location San Francisco, California
* Type Full-time
* Posted
11 November 2026

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The role, as published## About the company

Our client is a technology company.## The role Raydar is recruiting for this role on behalf of our client. Lead a research agenda in offline reinforcement learning, taking ideas from initial question through to shared findings. The position prizes scientific depth and judgment over engineering breadth, and pairs you with a more established colleague while leaving space to chart your own path.##

What you'll do
* ** Drive offline reinforcement learning
** research from start to finish, including choosing which questions to pursue and communicating the outcomes.
* Raise the performance of learned control policies on internal evaluation suites and build on earlier policy work.
* Train models on large, uneven-quality collections of data where feedback is scarce, applying several value estimation approaches.
* Investigate model-based methods and learned environment models for continuous control.
* Examine what keeps reinforcement learning training stable as data, compute and model scale increase.
* ** Design rigorous experiments
** with dependable baselines and watch findings get tested on physical robots.## What we're looking for
* Background in reinforcement learning research, in a research or applied scientist capacity, connected to generative visual models.
* A record of papers accepted at leading machine learning or robotics venues.
* Depth in core and offline reinforcement learning topics, such as value estimation, goal-directed learning, policy design and training stability at scale.
* Familiarity with model-based methods for continuous control or with multimodal value estimation.
* An advanced degree (PhD or master's) in machine learning, computer science or an adjacent area, centered on reinforcement learning.
* Ability to work on-site six days a week.## Bonus points
* Prior exposure to visual generative models applied to robotics.
* Time spent doing research at a top-tier AI organization.
* Contributions to publicly shared reinforcement learning codebases.
* Experience with large-scale simulation, sim-to-real transfer or robotics, including JAX.## Benefits
* Health, dental and vision coverage## Location and work model
* San Francisco, CA, United States
* On-site, 6 days per week in office
* Full-time## Compensation, as the posting describes it
* Equity Pay $200k to $350kUSD base a year