Staff Reinforcement Learning Research Engineer
Boston Dynamics1 month ago
Waltham, MA, USAStaff+
Base Salary
$155k - $200k/yr
Responsibilities
- Implement on-policy and off-policy reinforcement learning algorithms.
- Scale GPU-accelerated simulation to generate millions of samples per second.
- Develop sim-to-real transfer pipelines for policies deployed on physical robots.
- Integrate reinforcement learning with VLAs to fine-tune and distill large multimodal policies.
- Make robot policy deployment fast, easy, reliable, and reproducible.
- Build visualization tools that enable data-driven research.
- Own and develop company-wide RL tools supporting humanoid and quadruped robots.
Requirements
- An MS with 3+ years of experience, or a PhD, in machine learning, robotics, or a related field.
- Experience deploying policies on physical robots with attention to latency, robustness, and safety.
- Expertise with RSL-RL, CleanRL, RLlib, or Stable Baselines.
- Expertise with Isaac Lab, MuJoCo, MjWarp, or MjLab.
- Proficiency in PyTorch and/or JAX, plus inference runtimes such as ONNX, Triton, or TensorRT.
- Solid software fundamentals including Bazel, monorepos, Docker, and CI/CD.
- Experience building production-grade RL training pipelines.
- Deep knowledge of GPU-accelerated physics simulation.
- Experience applying RL to humanoid locomotion, whole-body control, or dexterous manipulation.
- Experience with sim-to-real transfer, domain randomization, or system identification.
- Experience with heterogeneous compute clusters and Kubernetes.
Benefits
- Medical, dental, and vision benefits.
- 401(k).
- Paid time off.
- Annual bonus structure.
- Ownership of the company-wide RL tools powering the company’s robots.
- Direct access to compute infrastructure for large-scale experiments.
Tech Stack
Categories
ML EngineeringRobotics