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Build and evaluate manipulation policies for Chef Robotics' food-assembly automation systems.

Chef Robotics is hiring a senior ML engineer focused on manipulation in San Francisco. The role designs and trains policies for robotic food handling, including imitation learning, reinforcement learning, diffusion policies, and transformer-based action models.
The listing is technical, but it is directly relevant to robot learning: the work turns production food-handling data, teleoperation, and evaluation pipelines into manipulation behavior that can run on real robots.
Food manipulation is a hard physical AI problem because the objects are inconsistent, deformable, and messy. Chef's production deployments make this a useful signal for anyone watching robot learning move beyond lab tasks into commercial operations.
About Chef Robotics
San Francisco physical AI company building robotic food assembly systems for commercial food production.
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