Type:

full-time

Job Description:

Technical Product Manager -

Robotics Data Location:

San Francisco, CA -

Hybrid Type:

Permanent Salary :

Open to negotiation The Opportunity We are working with an innovative applied R D organisation developing next-generation humanoid robotics and the software infrastructure that enables robots to operate effectively in the real world. The organisation is building across the full robotics stack, including hardware, locomotion, autonomy, simulation and data infrastructure, with a strong focus on moving research from the lab into real-world applications. They are now looking for a Technical Product Manager / Technical Program Manager - Data to take ownership of how robotics data is collected, managed and ultimately used by research and engineering teams. This is a highly hands-on role. You will sit at the intersection of robotics research, engineering, data and field operations, translating research requirements into practical data-collection programmes and ensuring the resulting datasets are high-quality, scalable and ready for downstream use. The Role You will own the end-to-end lifecycle of robotics data collection programmes - from understanding what researchers need, through designing collection processes and managing operations, to delivering high-quality datasets. You will work closely with researchers, robotics engineers, data engineers and operators, acting as the link between technical requirements and real-world execution. This is not a traditional programme management role. You will be expected to get into the detail, troubleshoot hardware and data issues, identify bottlenecks and build practical solutions. Key Responsibilities Own the end-to-end lifecycle of robotics data collection programmes, from research requirements through to delivered datasets. Translate research objectives into clear data-collection protocols, task definitions and quality standards. Coordinate data-collection operations across multiple sites, teams and teleoperators, managing throughput, quality and cost. Work closely with engineering teams to develop and improve pipelines handling high-fidelity robotics data, including video, sensor data, robot logs and teleoperation trajectories. Set up, maintain and scale physical data-collection rigs and associated hardware. Establish and monitor operational KPIs including data throughput, yield, cost per hour of data and turnaround time. Identify operational and technical bottlenecks and take ownership of developing solutions rather than simply reporting issues. Establish robust processes for data QA, ensuring data remains high-quality from initial collection through to its use in model training. Work closely with research and engineering teams to understand why datasets are failing and continuously improve collection processes. Keep researchers, engineers and field/operations teams aligned around priorities, requirements and delivery timelines. Build scalable workflows and systems that can support increasing volumes of robotics data collection. What We're Looking For We're looking for someone who combines technical understanding with strong operational and programme-management capability.

You will ideally have:

A strong track record of managing technical programmes with real operational complexity. Experience working hands-on with both hardware and data, with the ability to understand a physical sensor/robotics setup as well as the associated data pipeline. Direct experience running or operating data-collection programmes, rather than purely managing them from a distance. A strong understanding of data quality assurance, from initial collection through to training-ready datasets. The ability to diagnose why data is failing, identify root causes and implement improvements. A highly data-driven approach, with experience defining metrics and using them to improve operational performance. Strong systems-thinking and process-design skills, with the ability to build workflows that can scale. High operational rigour and a strong bias towards action, particularly within ambiguous or rapidly changing environments. Excellent communication skills, with the ability to work effectively across research, engineering and field/operations teams. Desirable Experience Experience in one or more of the following would be advantageous: SQL and/or Python, with the ability to independently interrogate data and build basic dashboards or analysis. Robotics, teleoperation, autonomous vehicles or large-scale physical-world data collection. Sensor calibration and the practical challenges associated with collecting reliable physical-world data. Computer vision, VLA models or machine-learning training data requirements. Managing distributed teams, remote operators or multiple data-collection sites across different locations/time zones. 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