Applied Scientist II, Reinforcement Learning
Amazon · Middlesex County, MA · 2 wk ago
EngineeringFull-time
Key job responsibilities
- Design and implement whole body control methods for balance, locomotion, and dexterous manipulation
- Utilize state-of-the-art methods in learned and model-based control
- Create robust and safe behaviors for different terrains and tasks
- Implement real-time controllers with stability guarantees
- Collaborate effectively with multi-disciplinary teams to co-design hardware and algorithms for loco-manipulation
- Mentor junior engineers and scientists
Basic Qualifications
- PhD, or Master's degree and 2+ years of applied research experience
- Experience with imitation learning and reinforcement learning for whole-body control
- Experience with methods such as hierarchical quadratic programming and model-predictive control
- Experience with simulation environments such as IsaacLab, Mujoco, Drake, etc.
- Experience with developing and deploying code for real-time controllers
- Experience in state estimation from multiple sensor modalities
Preferred Qualifications
- Experience programming in Java, C++, Python or related language
- Experience working effectively across cross-functional teams and partnering well with people at all levels within an organization
- PhD in Robotics, with a focus on whole-body control
- Experience with low-level joint torque/impedance control
- Experience with teleoperation systems
- Experience with robotics frameworks for fast prototyping (Matlab, ROS, etc.)
Benefits
- Comprehensive benefits including health insurance, medical, dental, vision, prescription, Basic Life & AD&D insurance, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage
- 401(k) matching
- Paid time off
- Parental leave