The role is part-time and contractor-based (1–2 days a week), with the option to ramp up. Minimum duration is 3 months, renewable. A great fit for a student.
Role Overview
Genesis is a global physical AI lab and full-stack robotics company. We build generalist robots to unlock unlimited physical labor, so humans can focus on creativity, curiosity, and what we love.
As a Robot Teleoperation Specialist, your primary responsibility is to operate robots during data collection sessions using teleoperation equipment. You’ll execute predefined tasks by following standard operating procedures, monitor robot behavior during operation, and ensure sessions are run safely and consistently.
This is a highly hands-on, execution-focused role. Technical setup, hardware maintenance, and data infrastructure are handled by other teams — when you arrive, everything is ready for you to teleoperate.
This role is onsite in Paris, FR.
Responsibilities
Operate robots using teleoperation equipment according to predefined tasks and SOPs
Execute teleoperation sessions reliably and consistently to support data collection
Observe robot behavior during operation and flag unexpected or unsafe behavior
Follow all safety guidelines to maintain a safe environment for yourself and the robot
Provide basic session feedback or notes when required
Maintain focus and quality during repeated teleoperation tasks
Collaborate with operations staff and follow direction from session leads
Requirements
Strong attention to detail and ability to follow instructions precisely
Comfortable working on your feet and using teleoperation or VR-style equipment
High consistency and reliability in executing repetitive tasks
Ability to stay focused for extended teleoperation sessions
Clear written and verbal communication skills
Coachable, curious, and open to feedback
Adaptable to changing task requirements in an R&D environment
Bonus Qualifications
Prior experience with robot teleoperation, simulation, or VR systems
Strong hand-eye coordination and spatial awareness
Ability to learn new physical tasks quickly and improve execution over time
