Amazon
Applied Scientist II, Reinforcement Learning
$143K–$193K
N.Reading, MA +1 · Full-time · Posted Sep 9, 2026
- Location
- N.Reading, MA
N.reading, MA - Experience
- 2+ years of CS, CE, ML or related field experience with a Master's degree; alternatively, a PhD is listed.
- Education
- PhD, or Master's degree and 2+ years of CS, CE, ML or related field experience.
About the job
Develop and deploy real-time whole-body control methods for robotic balance, locomotion, and dexterous manipulation, creating safe behaviors and collaborating on hardware and algorithm design.
What you'll do
- Design and implement whole-body control methods using learned and model-based control.
- Create robust, safe behaviors and implement real-time controllers with stability guarantees.
- Collaborate across disciplines on hardware and algorithms, and mentor junior engineers and scientists.
What they ask for
- PhD, or Master's degree and 2+ years of CS, CE, ML or related field experience.
- Experience with imitation learning and reinforcement learning for whole-body control.
- Experience with hierarchical quadratic programming, model-predictive control, and simulation environments such as IsaacLab, Mujoco, or Drake.
- Experience developing and deploying real-time controller code and estimating state from multiple sensor modalities.
Nice to have
- Experience in Java, C++, Python, or a related language.
- Experience with robotics frameworks for fast prototyping (Matlab, ROS, etc.).
Pay
142,800.00 - 193,200.00 USD annually (base salary)
Tools
IsaacLab, Mujoco, Drake, Java, C++, Python, Matlab, ROS
AI focus
Applies imitation learning and reinforcement learning to whole-body robotic control, including locomotion and dexterous manipulation.
Model-written summary · the original posting is authoritative