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.