Research Engineer (Simulation)

InLoop builds warehouse robots that run fully autonomously in customer warehouses today. The fleet is growing quickly (20+ robots), and the demand is huge.

We're hiring a research engineer to make our robots learn precise, contact rich tasks in simulation and carry them over to real hardware. You will be working on the real customer use-cases, and getting the best feedback, directly in a field.

This is research that ships. What you train runs on real robots in weeks, not years.

What you'll work on

• Manipulation with RL. Train reinforcement learning controllers for precise manipulation tasks.
• Sim to real. Get policies trained in simulation working on our real arms, and close the gap when they don't.
• Control. Combine learned policies with classical and learned control where it makes the robot more precise or safer.
• Into the stack. Bring what works into our autonomy stack so it runs on the fleet.

What we're looking for

• Hands on RL for robot control, trained in simulation and run on real hardware
• Large scale simulation (Isaac Sim, Isaac Lab, MuJoCo or similar)
• Strong control fundamentals
• A track record of shipping: code on real robots, papers or open source

Nice to have

• Experience with Vision language action models or imitation learning
• Experience with Code-as-a-Policy
• PhD with a track record of publications (CVPR, ICRA, ICLR, CORL, and etc.)

How to apply

Apply here and include a link to a policy you trained running on a real robot, a paper or a repo. That tells us more than a CV.