Applied Research Lead, Reinforcement Learning
RunwayFull Time
Junior (1 to 2 years)
Candidates should possess an MS or PhD in Computer Science, Robotics, Machine Learning, or a related field, and experience training and deploying reinforcement learning policies for complex behaviors, either in simulation or on real robots. Familiarity with modern ML frameworks and tools such as PyTorch, TensorFlow, and Ray RLlib is also required, along with a strong foundation in algorithm design, debugging, and performance optimization.
As a Research Scientist, you will design, train, and deploy reinforcement learning models to tackle challenging mobile and bimanual manipulation tasks, develop high-quality, production-ready code in Python and C++, test and iterate your models directly on real robot hardware, and collaborate closely with expert engineers and researchers through design reviews and hands-on experimentation. You will also contribute to a growing body of work shaping the future of humanoid robotics.
Develops advanced robots for industrial applications
Boston Dynamics creates advanced robots that enhance human capabilities and safety, focusing on legged robots with high mobility, dexterity, and intelligence. Their flagship products, Spot and Pick, are designed for commercial, industrial, and research applications, performing tasks that are dangerous or physically demanding for humans. Spot, for example, is a 65-pound robot that can navigate complex terrains and avoid obstacles autonomously using built-in AI. Unlike many competitors, Boston Dynamics emphasizes responsible use of their robots, limiting sales to commercial and research clients and ensuring high-quality standards through domestic manufacturing. The company's goal is to improve safety and efficiency across various industries while exploring future consumer applications.