Research Engineer, Robotics & Embodied AI

About the role

**Summary:**

Meta Reality Labs Research (RL Research) is a team of researchers and engineers pushing the frontier of AI, robotics, and AR/VR technology. Within RL Research, our team is building the next generation of foundation models (VLAs, WAMs) for robotic manipulation. We are looking for a skilled Research Engineer to take those models onto real hardware in our lab.This role covers the full robotics stack: hardware bring-up, teleoperation, data collection, and running learned policies on real robots. It involves building prototypes together with research scientists and engineers, running the experiments that show whether they work, and finding the problems that only appear once a model has to act in the physical world.

**Required Skills:**

Research Engineer, Robotics & Embodied AI Responsibilities:

1. Build, operate, and maintain robot platforms for teleoperation and deployment

2. Deploy learned policies on real robots and optimize their performance on-robot

3. Work with researchers to design experiments and measure how well policies work on real hardware

4. Debug failures across hardware, perception, data, and policies

5. Turn research results into working prototypes

6. Build tooling that makes experiments repeatable

7. Publish research results in top conferences and release code that contributes to the field of robotics

**Minimum Qualifications:**

Minimum Qualifications:

8. Currently has, or is in the process of obtaining, a PhD degree in robotics, computer vision, machine learning, or a related field

9. Industry experience with modern, general-purpose robot platforms

10. Hands-on experience bringing up, calibrating, and debugging a new robot platform from scratch

11. Experience running learned policies on real robots and improving their performance

12. First-author publications at ICRA, CoRL, RSS, IROS, or CVPR, or widely used open-source contributions

13. Proficient in Python and PyTorch

**Preferred Qualifications:**

Preferred Qualifications:

14. Contributed to open-source robot learning projects such as LeRobot, robosuite, or ManiSkill

15. Trained or evaluated large 3D generative or world models

16. Built teleoperation rigs and used them to collect robot data at scale

17. Debugged policy failures across hardware, data, training, and simulation

18. Worked on long-horizon planning for robots

19. Worked on 3D computer vision for robots, such as reconstruction, pose estimation, or scene understanding

20. Worked on contact-rich manipulation, including force or tactile feedback

21. Trained or fine-tuned vision-language-action models or world action models

22. Fluent in ROS or ROS 2, including kinematics and camera-to-robot calibration

**Industry:** Internet

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Virtual, USA

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