Machine Learning Engineer

What you'll be doing: You’ll develop and deploy learning-based methods for robot control and object manipulation across a fleet of industrial robotic cells. You’ll use multi-modal data, including images, force and torque, to make robots more capable, reliable and adaptive. You’ll design and build vision-language-action (VLA) models, and shape strategy across the whole solution lifecycle: data collection, fleet learning and continuous learning. You’ll work closely with hardware and software teams to integrate manipulation, control and planning algorithms into production robotic platforms, and help keep the team at the frontier of robot learning.

What we’re looking for: PhD or Master's in Robotics, Mechanical Engineering, Electrical Engineering, Computer Science or a related field A track record of publishing at top venues (e.g., NeurIPS, ICLR, ICML, CoRL, RLC) Hands‑on experience applying machine learning to robot manipulation Experience building models from scratch and deploying them in real-world applications, not just research or sim A proven track record of deploying scalable solutions for autonomous robotic systems Experience with robotic simulation tools such as Isaac Sim or MuJoCo Experience with pose estimation, segmentation, active perception and affordance-based bin picking Strong programming skills in Python and/or C++ Clear communication: you can explain complex technical ideas to a wide range of audiences The bottom lineIf your background is real robot learning, real hardware, and models that leave the lab and do real work, and you want your policies improving every day on a fleet of production robots, we’d love to talk. We encourage candidates from underrepresented groups to apply even if you don’t check every box. Research shows women and underrepresented candidates often leave themselves out of roles they’re qualified for. If this sounds like your kind of problem, we want to hear from you.