Robot Operator, Data Collection

About Mind:

Mind Robotics is building Physical AI for real-world industrial deployment, starting with the factory floor. We believe the hardest problems in AI are solved when researchers and engineers are hands-on with the physical world every day - and we're looking for people who are passionate about robotics, value ownership, and are excited to tackle difficult problems.

About the team and the role:

The Data Collection team owns the raw material our foundation models are trained on. We pilot robots through real industrial manipulation work. The skills could be pick and place, sorting, fastening, seating connectors but then we turn those hours into the demonstration data our models learn from. With Rivian as our first manufacturing partner, we are emulating the live, high-variability work inside an active production facility.

As a Robot Operator, you are the person actually showing the robot how the work is done. You'll spend your day on the floor running robots through tasks, some routine, some brand new, some that don't work yet and need figuring out. Along the way you will be developing judgment about what separates a good demonstration from a bad one. You'll be closer to the hardware than anyone at the company, which means you'll be the first to know what's awkward, what's unsafe, and what should change. We're early, so the process you learn this month may get rewritten next month, usually because someone on the team found a better one.

Responsibilities:

• Pilot the robots. Operate leader/follower rigs and other control setups to run robots through industrial manipulation tasks: pick and place, bin sorting, fastener driving, connector seating, tool use.

• Produce data the models can learn from. Execute repeated demonstrations to a consistent standard — clean motion, consistent framing, sensible recovery when something goes wrong — and develop the eye to tell a usable episode from an unusable one.

• Own the quality of your own output. Review, label, and flag your own bad episodes rather than letting them through, and keep clear session logs another person can act on.

• Work safely, so we can work fast. Run pre-power-up safety checks, know where the stop is, follow lockout procedure, and raise concerns early. Careful people let us move quickly.

• Run new tasks from a cold start. Take an unproven task description, work out a repeatable approach on the hardware, and document what you found.

• Feed findings back into how the work is designed. Report rig ergonomics problems, ambiguous instructions, and task setups that don't survive contact with reality to the engineers and researchers who own them.

• Help the next person. Train new operators on tasks you've mastered and sharpen the written procedures as you go. There's a clear path toward owning task areas and training operators — that's the growth we expect, not a day-one expectation.

• Expect to be on your feet and moving for roughly 5–6 hours of the day. Operating the rigs is sustained, full-body work: reaching, bending, crouching, twisting, holding position, and extended use of both arms and hands. Come ready for that.

• This is not a lifting role. There is no significant lift or carry requirement. The demand is sustained manipulation and posture, not strength.

• We can accommodate seated and wheelchair-based operators. Our control setups can be operated seated, and we're willing to adapt rigs, station height, and task assignment to make that work. If you use a wheelchair or have other accessibility needs, this role is open to you.

Requirements:

• Roughly one year or more of work history where you were accountable for your own output: showed up on time, held to a standard, dealt with the consequences when something went wrong. The industry doesn't matter; having been held to a bar does. No degree required — relevant hands-on experience or equivalent experience is what counts.

• Genuine interest in robots and AI. You don't need expertise. You do need to want to know how the thing works, and to get a little excited when it does something new.

• A demonstrated safety mindset. Steady around powered equipment, follows procedure without being watched, comfortable stopping work to raise a concern.

• Strong hand/eye coordination and spatial reasoning. You pick up physical skills quickly and can explain what makes one approach better than another.

• Tolerance for high-repetition work at a consistent quality bar across a full shift.

• Clear, plain written communication. Enough to log what happened in a session so someone else can understand and act on it.

• Comfort with direct feedback, both getting it and giving it.

• Tolerance for change. Early-stage means unfinished. If that sounds fun rather than stressful, that's a good sign.

• Authorization to work on-site in Palo Alto, CA for a role that cannot be performed remotely.

• Experience with humanoid or mobile robots, VR/AR systems, or motion capture is a plus

• Exposure to how ML training data is produced is a plus

• Light scripting (Python or shell) is a plus

• Teaching or coaching experience is a plus

• Shift work in a safety-sensitive setting is a plus

• Time in a manufacturing or production environment is a plus