Data Collection Operations Lead

ABOUT REVEL REVEL is an AI robotics company developing physical intelligence for general-purpose humanoid robots. We capture the force, dexterity and intent of human work with our Neural Gambit wearable, and use it to train RAI, the intelligence that powers our robots. REVEL is headquartered in Palo Alto, California, with R&D and engineering facilities in Prague and Hradec Králové, Czech Republic. This role is on-site with our engineering team in the Czech Republic. THE ROLE The LEGO data engine is how REVEL generates high-quality human demonstrations at scale. We are looking for a Data Collection Operations Lead to own the day-to-day operation and continuous improvement of our human data-collection pipeline. You will work at the interface between biomedical engineering, experimental science and robotics. Working closely with the sEMG/biomedical engineering and ML/robotics teams, you will translate experimental protocols into reliable operational processes, coordinate data-collection operators, maintain high standards of data quality, and continuously improve throughput. This is a hands-on operational leadership role. You will spend significant time on the data-collection floor, not only managing from a desk. RESPONSIBILITIES - Own day-to-day operation of REVEL's human data-collection facility/workstation. - Translate experimental protocols developed with biomedical/robotics scientists into clear, executable SOPs for operators. - Plan and coordinate data-collection sessions, staffing, participant/operator schedules and workstation utilization. - Recruit, onboard and train data-collection operators. - Define and enforce standards for: - sensor/wearable setup - participant preparation - protocol execution - data labelling - metadata capture - data-quality control - equipment handling. - Monitor data quality, throughput, failure rates and operator performance using appropriate operational metrics. - Identify systematic sources of bad data and work with the engineering/science team to eliminate them. - Own the feedback loop between the data-collection floor and the biomedical/ML teams. - Coordinate rapid iteration of collection protocols when experimental requirements change. - Develop processes that make high-quality data collection repeatable across operators and across shifts. - Troubleshoot operational, hardware and workflow problems and coordinate escalation to engineering when necessary. - Maintain documentation and version control of collection SOPs and operational procedures. - Ensure that changes to protocols are consistently communicated and implemented. - Build processes for identifying and rejecting low-quality recordings before they enter downstream ML pipelines. - Help establish realistic capacity and throughput targets as the data engine scales. - Drive continuous improvement in quality, throughput, reproducibility and operator efficiency. -…