This position focuses on building real-world datasets essential for training robotics systems. As a Robotics Data Generalist, you will engage in structured data capture sessions aimed at generating high-quality training data for embodied AI systems. This is an opportunity to contribute directly to the development of Physical AI while participating in guided protocols that involve performing various physical tasks in controlled environments.

• Participate in structured data capture sessions under guided protocols.
• Perform a range of everyday interaction and manipulation tasks.
• Follow detailed instructions to ensure consistency across recordings.
• Help maintain organized data capture workflows.
• Collaborate with a small team dedicated to building high-quality robotics datasets.

• Strong attention to detail.
• Ability to follow structured protocols carefully.
• Reliability and consistency across repeated tasks.
• Interest in robotics and physical AI systems.
• Availability for scheduled data capture sessions.
• Previous robotics experience is helpful but not required.

This is a paid opportunity, with hourly compensation ranging from $15 to $45. Sessions will take place near major universities, and candidates must be able to attend in-person.

Hourly pay between $15 and $45.

Participants must be able to attend data capture sessions near the following universities: Stanford University, University of California, Berkeley, UCLA, University of Southern California, Carnegie Mellon University, Georgia Institute of Technology, The University of Texas at Austin, University of Illinois Urbana-Champaign, University of Michigan, Purdue University, Virginia Tech, and Arizona State University.

Multi-session participation is preferred, and this role is designed for a small, selective cohort contributing to datasets that advance robotics research.