Technical Product Manager, Data

About the role

The Technical Program Manager will own the end-to-end lifecycle of robotics data collection programs, from defining research requirements to delivering high-quality datasets. This role requires hands-on involvement in setting up and maintaining physical collection rigs, designing data pipelines, and aligning stakeholders across research, engineering, and field teams.

Responsibilities

• Own the end-to-end lifecycle of robotics data collection programs, from research requirements to delivered datasets.
• Translate research goals into concrete collection protocols, task designs, and quality bars.
• Run collection operations across multiple sites and teleoperators, keeping throughput, quality, and cost on track.
• Partner with engineering to build and improve pipelines for high-fidelity sensor data such as video, robot logs, and teleop trajectories.
• Define and track key performance indicators (KPIs) like throughput, yield, cost per hour of data, and turnaround time.
• Find bottlenecks and build fixes to ensure smooth operation.
• Keep researchers, engineers, and operators aligned on priorities and timelines.

Requirements

• Track record running technical programs with real operational complexity.
• Comfort in the weeds of both hardware and data.
• Has personally run hands-on data collection before, not just managed it from a distance.
• Strong grasp of data QA across the full path from collection to training, and can diagnose why data is failing and iterate it from unusable to training-ready.
• Data-driven mindset. Measures what you run and improves it.
• Strong systems thinking and process design. Builds workflows that hold up at scale.
• Operational rigor and a bias for action in ambiguous, fast-moving conditions.
• Clear communication across research, engineering, and field teams.

Qualifications

• Track record running technical programs with real operational complexity.
• Comfort in the weeds of both hardware and data.
• Has personally run hands-on data collection before, not just managed it from a distance.
• Strong grasp of data QA across the full path from collection to training, and can diagnose why data is failing and iterate it from unusable to training-ready.
• Data-driven mindset. Measures what you run and improves it.
• Strong systems thinking and process design. Builds workflows that hold up at scale.
• Operational rigor and a bias for action in ambiguous, fast-moving conditions.
• Clear communication across research, engineering, and field teams.

Skills

• SQL or Python, enough to pull your own data and build your own dashboards.
• Experience with robotics, teleoperation, autonomous vehicles, or large-scale data collection.
• Familiarity with sensor calibration and the realities of capturing physical world data.
• Exposure to VLA models, computer vision, or ML training data requirements.
• Experience coordinating distributed teams or collection sites across time zones.

Benefits

Menlo Research is an equal opportunity employer and does not discriminate on the basis of any legally protected characteristic. Menlo provides reasonable accommodations during the application process. If you need one, please let your recruiter know.

Pay

Competitive salary and benefits package.

Schedule

Full-time position.