Embodied AI jobs

Working in Embodied AI

What work does embodied AI involve?

Embodied AI connects learned representations and decisions to a physical system. When evaluating a role, distinguish policy research from robot deployment, data collection and evaluation: these can require very different day-to-day skills even when the employer uses the same product language.

Build evidence of a complete learning loop

A useful portfolio project connects observations to actions and measures performance on held-out tasks. Describe how demonstrations were collected, what changed between training and evaluation, and where the policy failed. Report task success and recovery behavior, not just an impressive video.

Questions to ask before applying

Ask which robot and sensor stack the team uses, whether the work is primarily simulation or hardware, and who owns evaluation and deployment. Check each listing for its actual degree and experience requirements; this page does not infer a universal PhD requirement.

Practical reference: LeRobot: data collection, policies and deployment. Guidance is editorial, not a frequency analysis of employer requirements.

How these jobs are selected

Matches explicit embodied/physical-AI or vision-language-action titles, plus robot-learning roles. Generic company descriptions are not used. This conservative selection is not a census of every embodied-AI job.

Compare advertised robotics salaries with sample sizes and methodology.