Some Humanoid Jobs Say Robotics Experience Isn’t Required. What Do They Want Instead?

Some robotics jobs are explicitly open to people without a robotics-company background

The obvious candidate for a Physical AI company is a robotics engineer. Many core roles still demand deep robotics experience. But not all of them do.

Figure's Mechanical Engineer, Structures - Robot Hands posting explicitly says robotics experience is not required. Instead it asks for end-to-end ownership of complex mechanical modules, testing and validation, NPI, supplier work, and failure analysis — with consumer electronics, EV and aerospace listed as relevant backgrounds.

Another Figure Hands role focused on compliant elements says the same thing, prioritizing elastomers, silicones, complex plastics and injection molding over a prior robotics label.

Why automotive, aerospace and consumer electronics keep appearing

Physical Intelligence's Robot Build Technician posting values experience in robotics, automotive, aerospace or consumer electronics. The work covers assembly, wiring, harnessing, sensor and actuator integration, quality checks and manufacturing root-cause analysis.

Those industries share a capability stack: building complex electromechanical hardware, controlling tolerances, working through suppliers, scaling production and diagnosing failure. Physical AI increasingly needs the same industrial muscle as it moves from prototypes to fleets.

For operator roles, the adjacency map gets even wider

Mind Robotics lists motion capture, simulation or VR studios, surgical robotics, drone operations, stunt work, advanced manufacturing and professional gaming or esports coaching among possible backgrounds for Robot Operators.

The common thread is not the label. It is precise physical control, repeatability, judgment, SOP writing, training and quality control that can be demonstrated in an operating environment.

Japan is opening lower-entry pathways as well

APTO's Physical AI Robot Operator role centers its requirements on basic PC use, noticing small deviations, handoffs, shift and safety rules, and Japanese workplace communication. A robotics degree or prior robot-operator job is not listed as mandatory.

Prox Industries' Robot Teleoperator requires conversational Japanese, basic PC skills and availability at least two days a week; teleoperation experience and robotics knowledge are preferred. This does not mean Japan's Physical AI market is becoming low-skill. High-skill robotics and simulation roles exist alongside these jobs. It means data collection is creating a different entry lane.

In the U.S., some teleoperation jobs say they will train from zero

FS Studio's Robotics Teleoperator posting states that no prior experience is required and that workers are trained from scratch. Operators use VR headsets, haptic gloves and controllers in a shift-based data-collection environment.

That is evidence of a frontline operations layer forming around Physical AI. It is not yet evidence that this will become a large, durable occupation; more autonomy could reduce repetitive teleoperation demand over time.

What companies are buying is evidence of solving physical problems

Across the postings, the recurring language is design, build, validation, reliability, quality, troubleshooting, SOP, safety, production, suppliers and integration.

That changes the career question from 'which industry were you in?' to 'what system did you own, what failure did you reduce, what hardware did you ship, and what process did you make repeatable?'

Adjacent does not mean equivalent

A Figure role saying robotics experience is not required does not mean every Figure job is open to non-robotics candidates. Its Systems Integration Engineer for the hand subsystem asks for five-plus years of hands-on work on robotic or electromechanical systems.

Requirements vary by role and hiring unit. One posting cannot be generalized to an entire company, let alone the whole market.

What this means for engineers in automotive and manufacturing

Engineers from automotive, industrial automation, semiconductor equipment and precision manufacturing may not need to erase their previous careers to enter Physical AI. Load and durability analysis, GD&T, NPI, supplier collaboration, root-cause analysis, quality and maintenance are appearing directly in current robotics postings.

The job is to translate that experience into the target role's language and close the remaining gap with real robot-system evidence where necessary. Physical AI's talent war may be partly about discovering that difficult experience already exists — just under a different industry name.