Staff Reinforcement Learning Research Engineer
Bostondynamics Open · verified Oct 22, 2026 At a glance
Senior AI Research role at Bostondynamics. Waltham Office · full-time · $155,284–$200,000 base.
aimlroles summary, based on the employer's posting.
What you'll do
- Build and maintain the RL pipeline, covering parallel simulation, domain randomization, policy optimization and robot deployment
- Implement both on-policy and off-policy learning, then scale GPU simulation to produce training samples
- Adapt simulated policies for physical robots and tune or distill multimodal policies using VLAs
- Make robot deployment quicker and more repeatable, and create visual tools for research decisions
What you bring
- A master's degree plus at least three years in ML, robotics or a related field, or a PhD in one of those areas
- You have put policies on physical robots while accounting for latency, robustness and safety
- You are skilled with RL toolkits, simulation and rendering systems, and PyTorch or JAX with inference runtimes
- You bring solid software engineering skills with Bazel, monorepos, Docker and CI/CD
Who this fits
This staff-level research engineering role suits you if you can connect reinforcement learning research with deployment on physical robots. The position is based at the Waltham office.
From the employer
Do you want to build the scalable reinforcement learning framework that powers the next generation of humanoid and quadruped robots? As a Staff RL Research Engineer, you'll own the RL stack, including massively parallel simulation, domain randomization, policy optimization, and on-robot deployment. Your job is to make the pipeline fast, reliable, and reproducible. You'll work alongside world-class engineers and scientists pushing the boundaries of whole-body control and dexterous manipulation.
In this role, you will:
Implement on-policy and off-policy learning algorithms
Scale GPU-accelerated simulation to generate millions of samples per second
Crack sim-to-real to produce policies that transfer to the physical robot
Integrate RL with VLAs to fine-tune and distill large multimodal policies
Make deployment easy, fast, and reproducible
Build visualization tools that enable data-driven research
Required Qualifications
MS with 3+ years of experience, or PhD, in ML, Robotics, or a related field
Deployed policies on physical robots with attention to latency, robustness, and safety
Expertise with RL toolboxes (RSL-RL, CleanRL, RLlib, Stable Baselines)
Expertise with simulation and rendering tooling (Isaac Lab, MuJoCo, MjWarp, MjLab)
Proficient in PyTorch and/or JAX, plus inference runtimes (ONNX, Triton, TensorRT)
Solid software fundamentals: Bazel, monorepos, Docker, CI/CD
The ideal candidate has:
Built production-grade RL training pipelines
Deep knowledge of GPU-accelerated physics simulation
Applied RL to humanoid locomotion, whole-body control, or dexterous manipulation
Worked on sim-to-real transfer, domain randomization, or system identification
Experience with heterogeneous compute clusters and Kubernetes
Why join us?
Ownership of the company wide RL tools powering all of our robots
Direct access to the compute infrastructure to run large-scale experiments
The chance to help define what’s possible in real-world robotics
The salary or hourly pay range for this position will be clearly stated in the job posting as required by Massachusetts law. The base pay range for this position is between $155,284.34- $200,000. Base pay will depend on multiple individualized factors including, but not limited to internal equity, job related knowledge, skills and experience. This range represents a good faith estimate of compensation at the time of posting. Boston Dynamics offers a generous Benefits package including medical, dental vision, 401(k), paid time off and an annual bonus structure. Additional details regarding these benefit plans will be provided if an employee receives an offer for employment.