Robotics Teleoperator

Job Summary As a Data Operations Technician, you will join the Product Data Operations team to support The Robotics Studio data collection and annotation projects. You will work directly with new and emerging VR/AR technologies, performing hands-on data collection, annotation, and quality assurance tasks. Responsibilities Operate prototype devices to collect high-quality data in lab and simulated environments. Follow detailed protocols to perform complex data collection tasks, ensuring consistency and accuracy.

Annotate and label collected data using internal tools and platforms. Participate in quality assurance (QA) activities, reviewing and validating data for accuracy and completeness. Collaborate with team members and project leads to orchestrate and optimize data collection sessions. Document procedures, issues, and findings as needed. Adhere to all safety, privacy, and confidentiality guidelines.

Minimum Qualifications

Experience with AR/VR devices, robotics, or similar hands-on technical environments. Strong attention to detail and ability to follow complex protocols. Comfort with repetitive tasks and ability to maintain focus and accuracy. Basic computer literacy; experience with data entry or annotation tools is a plus. Ability to work collaboratively in a fast-paced, on-site team environment. Willingness to learn and adapt to new tools and processes.

Scope of Work and Deliverables Generate high-quality datasets following strict procedural instructions.

Preferred Qualifications Strong experience operating Meta Quest 3 headsets Experience troubleshooting and documenting technical errors

Roles & Responsibilities Operate and set up prototype robotics and XR devices (e.g., Quest 3 headsets) according to established protocols. Execute hands-on data generation tasks, ensuring accuracy and consistency. Annotate and review collected data using internal tools, maintaining high quality standards. Perform initial quality checks and flag issues for follow-up. Collaborate with team members and project leads to support data operations and troubleshoot device or process issues.

Adhere to safety, privacy, and operational guidelines in all lab activities. Surrounding team & key projects Meta Robotics Studio (MRS) needs to train models to operate humanoid robots. Due to the nascent, but very high-priority status of the program, the Product Data Operations (PDO) supporting MRS needs a very adaptable workforce of trusted personnel who can interact directly with early-prototype devices and provide real-time feedback on dataset generation processes.

The collection and annotation processes will be very iterative for a period of time as MRS dials in on what data they need and how they want to evaluate that data. This group will serve as a foundational group for establishing long-term, scalable collection and annotation projects through traditional Scaled Ops (SO) resources. Typical Day-to-Day in the role This role will spend their day on-site preparing and operating devices, following detailed protocols to generate and log data, performing initial quality checks, and using internal tools to annotate or review data.

The role involves repetitive but detail-oriented tasks, close collaboration with team members, and regular communication with project leads to ensure high-quality, consistent data for model training and evaluation. How will performance be measured? Can you walk me through the evaluation process for this role, and how you assess the impact and effectiveness of a Reality Labs Project Manager’s work? Performance will be measured by the individual’s ability to consistently execute data operations protocols with accuracy and attention to detail, maintain high data quality standards, and reliably support device setup, operation, and troubleshooting.

Evaluation focuses on meeting daily and project-based targets for data generation and annotation, following safety and operational guidelines, and contributing to a collaborative team environment. The process includes regular check-ins with the manager, feedback on task execution and data quality, and periodic reviews of productivity, reliability, and…