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Robotics Manipulation Engineer

Pubblicato il 10-09-2026 - Embodied Ai in Roma

About The Role
We are looking for an engineer to own the path from data collection to a working robot, together with the interface someone can use to drive it. You will integrate a robot learning stack — LeRobot, DAgger, RL, ACT/diffusion policies, VLAs — into our distributed system, and own customer-facing manipulation capabilities end to end: choosing the approach, making the robot actually do the task, and being there when it is demoed.
This role is for library and framework integrators rather than from-scratch builders. We value engineers who pick the right off-the-shelf piece and integrate it cleanly. The work spans ML pipelines on one side, real product UI on the other, and a distributed system in between. Show and tell is part of the job, and we hire people who naturally build toward something visible.
You will join a fast-growing robotics and AI team building solutions to real-world problems.
What you'll do
- Own manipulation capabilities end to end: define the task, design the data collection, train and evaluate the policy, get it running on the robot,



and demo it live to customers.
- Integrate robot learning libraries (LeRobot, DAgger, RL, ACT/diffusion policies, VLAs, NVIDIA Isaac) into our training and deployment pipelines.
- Debug real manipulation failures — grasp failures, calibration drift, distribution shift between collection and deployment — and decide whether the fix is more data, a different policy, or a change to the setup.
- Wire ML artifacts and tooling (W&B;, HF Hub, GCS) into the systems that actually run on robots.
- Build and improve the teleoperation and data-collection interfaces that make good demonstration data possible.
- Use simulation when it speeds things up and real robots when it does not.

What you bring
- A track record of integrating complex libraries and frameworks into working systems, including an understanding of their failure modes rather than only their happy path.
- Experience integrating ML libraries into real software

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