Robot Operator Lead
Mind Robotics - Palo Alto, California, United States
Posted May 18, 2026
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- Verification
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- Salary
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- 401(k) match
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Schedule
- Shift type
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- Weekend work
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Application
- Cover letter
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- Assessment
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- Deadline
- Not stated
Where they hire
State eligibility is not yet verified.
About this role
Robot Operator Lead Palo Alto, California, United States Mind Robotics is building the operational backbone behind general-purpose industrial robots - the data, the procedures, and the people who teach machines how to move through the real world. Our operators are the human side of that loop: they pilot robots, generate the demonstration data that trains our models, and surface the edge cases the AI team needs to see. We're hiring several Teleoperations Leads to drive that function end-to-end. This is a hands-on lead role, not a desk job. You'll spend a meaningful share of your week teleoperating robots, running collection sessions, and working through new tasks yourself before anyone else does. Then you'll turn what you learned into SOPs, train the operators behind you, and raise the bar on data quality across the team. Responsibilities Operate. You'll pilot our robots through new and existing behaviors - household manipulation, commercial workflows, dexterous tasks, recovery maneuvers. You're the person who figures out how a new task should be performed before it's written down. Write the playbook. Every recurring task, bring-up procedure, shutdown sequence, safety check, and data-collection protocol becomes an SOP under your ownership. You'll define what "good" looks like - pose conventions, framing, retry behavior, when to abort a take - and keep those documents alive as the platform evolves. Train the team. You'll onboard new operators, run shadowing sessions, certify them on each task class, and run periodic calibration reviews to catch drift. When a new behavior comes online, you're
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