Senior Machine Learning Engineer (Tech Lead), Robot Learning, Loco- Manipulation

What you'll do

• Set team ML direction and own architecture and research workstreams across action-policy learning, world-model supervision, and policy orchestration.
• Design hybrid physics-ML architectures integrating manipulation, locomotion, and whole-body control; guide phased deployment with partner teams.
• Write code, mentor engineers, and establish team engineering practices and standards.

What they ask for

• 5+ years of hands-on robot learning experience, including shipping sim-to-real policies on real robots across different tasks or platforms.
• Demonstrated technical leadership and mentorship, including architectural decisions others built on.
• Deep sim-to-real expertise and full-stack robot-learning experience, from simulation and training through deployment and failure diagnosis.
• Strong Python and C++ programming skills; Ph.D. or Master's in a relevant field or equivalent experience.

Nice to have

• Edge inference experience, including TensorRT, ONNX, or edge-class deployment.
• Loco-manipulation experience on legged platforms, or precision manipulation or surgical robotics experience.

Tools

Python, C++, TensorRT, ONNX, PINNs, neural ODEs, MPC

AI focus

Develop robot-learning and hybrid physics-ML systems for whole-body loco-manipulation, including policy learning, world-model supervision, and real-world deployment.