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 systems (research code into something closer to production).
- Solid frontend skills, ideally React with TypeScript. You can ship a usable interface.
- A taste for distributed systems, and an understanding that the model is one component among many.
- A show-and-tell instinct. You build to demo rather than to spec.
Bonus Points
- At least two years at a robotics, IoT, or in-field-devices company. We would like at least one person on the team to have this background.
- Experience with ROS2.
- Hands-on experience with LeRobot, DAgger, or RL.
- Experience with WebRTC, GStreamer, or other real-time, low-latency systems.
- Experience with WebXR or immersive teleoperation interfaces.
- Experience with robot simulation (Isaac, MuJoCo, or similar).
- Customer-facing experience in demos, on-site integration, or technical pre-sales.
Why Join Us?
Join us in reinventing how robots can be integrated into society through safe, intelligent, and innovative robotic solutions.
At Embodied AI, you will have the opportunity to work on cutting-edge soft robotics technologies and contribute directly to the development of robots that can safely interact with people and operate in complex real-world environments.
If you are a motivated engineer with a passion for robotics and technology, eager to take ownership of challenging technical problems and grow within a fast-paced robotics startup, we would love to hear from you.
Embodied AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
