Senior Robot Learning Engineer

Senior Robot Learning Engineer (Manipulation)

Chicago, IL| On site | Up to $200k + equity | Visa sponsorship and relocation support

The company

A well funded robotics company building AI powered robots to support the labor workforce.

The role

You’ll own how the robots learn and perform physical skills: the data pipeline that captures how people do the work, the policies that learn from it, and the executor that runs every action on the robot, classical or learned, behind one interface.

What you’ll do

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• Define how demonstrations are captured: teleop rigs (leader arms, VR) and egocentric capture of people doing the work
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• Own the robot learning data pipeline: synced observations and actions, labelling, dataset versioning and quality checks
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• Set the policy architecture: a shared vision and force backbone with task conditioned heads, so a new skill needs a few demos, not a new model
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• Train with imitation learning, diffusion or transformer policies and VLAs, using RL where the reward is clear
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• Build the training and evaluation loop in sim and on real robots, with held out evals that gate deployment
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• Solve manipulation of deformable materials: cable, tape, membrane
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• Own the actuate executor, with classical control and learned policies behind one contract so the planner can pick either
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• Build the compliance layer for contact rich work (nailing, pressing, taping, insertion) with force and impedance control
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• Deploy policies on the robot within real time and safety limits, and build recovery for common failures
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• Lead and mentor learning and manipulation engineers, while still writing production code and testing on real robots every week
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What you’ll bring

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• 5+ years in robotics or ML, including learned manipulation policies deployed on real hardware
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• Deep experience with imitation learning and RL, and a clear view of when to use each
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• Force and impedance control for contact rich manipulation
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• Built a robot learning data pipeline: teleop capture, labelling, versioning, evaluation
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• PyTorch from dataset to deployed policy
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• Strong Python and C++, ROS2, Linux, Docker, CI/CD
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• A record of setting technical direction and mentoring engineers
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Nice to have

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• MS or PhD in Robotics, ML or CS
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• VLAs or other robot foundation models
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• Diffusion Policy, ACT or similar visuomotor architectures
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• Deformable object manipulation (cable, textile, tape)
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• Bimanual or dexterous manipulation
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• Sim to real with Isaac Sim or MuJoCo
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• Teleop systems: leader/follower arms, VR, egocentric capture
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• Datasets in MCAP or rosbag
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• Contact rich assembly, finishing or construction work
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What’s on offer

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• Base salary up to $200k
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• Equity
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• Comprehensive benefits
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• Visa sponsorship and relocation support
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• Direct access to robots, sensors and manufacturing environments every week
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• A rare problem: teaching robots the trades that build homes, on factory and field hardware
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