Reinforcement Learning Engineer- Spot Behavior

Do you have a passion for applying machine learning to drive real-world robot behavior? As a Reinforcement Learning Engineer on the Spot Behavior team, you will develop and deploy cutting-edge reinforcement learning techniques to expand Spot’s capabilities in dynamic, real-world environments. You’ll work on a multidisciplinary team tackling high-impact mobility challenges—ranging from terrain traversal and balance to complex locomotion behaviors. This role offers the opportunity to work hands-on with Spot and push the boundaries of legged robot performance.

Day-to-Day Activities

• Design and deploy reinforcement learning systems to improve Spot’s mobility and robustness.
• Integrate learning-based solutions into Spot’s existing planning and control systems in collaboration with experts across controls, perception, and planning.
• Build and maintain systems that support reliable, scalable, and reproducible RL training.
• Test and debug your work using our in-house fleet of Spot robots.
• Write high-quality, maintainable code in both Python and C\+\+.
• Provide mentorship and technical guidance on ML best practices.

We Are Looking For

• Master’s degree or higher in Robotics, Mechanical Engineering, Computer Science, or a related field.
• 3\+ years of experience with a proven track record of deploying models on hardware.
• Proficiency in both Python and C\+\+ programming languages.
• Strong analytical and debugging skills.
• Familiarity with modern deep RL toolkits and architectures.

Nice To Have

• Experience with legged robotics.
• PhD in Robotics, Mechanical Engineering, Computer Science, or a related field.