Boston Dynamics
Reinforcement Learning Engineer- Spot Behavior
Boston Dynamics - Washington, District Of Columbia, United States, 20421
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Overview
Reinforcement Learning Engineer
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 challengesranging 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.
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 challengesranging 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.