About the Role

Frontier AI is going physical, and the labs building robot foundation models are bottlenecked on real-world data — but no one agrees yet on what to collect, how to capture it, or how to tell whether it helped. The problems to solve in the industry are wide open.

As Research Product Manager, you’ll run our research-led go-to-market: the benchmarks, publications and post-training results that show labs where their models fall short and what data closes the gap. You’ll work researcher-to-researcher with frontier robotics and embodied AI labs, turn those conversations into pilot briefs for data types that don’t exist yet, and hand them to Product to build. You’ll work directly with our research lead on what we publish and what we keep.

What You'll Do

Build trusted relationships with researchers and with the stakeholders who control spend at frontier robotics and embodied AI labs, and be their technical point of contact

Advise customers on robotics data for both pre-training and post-training, from egocentric video, teleoperation, tactile capture to model evaluation.

Run the benchmark and publication roadmap with our research team

Co-design pilot prototypes and define requirements with researchers across task and environment mix, capture configuration, annotation and QC criteria, delivery format, and the success metrics

Get hands-on with the data in our robotics lab from inspecting early samples, playing back data on robotics, and doing quality evaluations yourself

Capture forward demand, predicting what labs will need in 6-12 months, and feeding it into the company’s roadmap

What We're Looking For

Hands-on technical background, with a background in engineering or research

Strong communicator who can influence and build trust amongst researchers

Prior work with researchers on pre-training or post-training data at a lab, model company, or data vendor

Fluent in how robot learning models are trained and evaluated today from imitation learning, world models, to VLA-style policies

Has scoped and landed external projects, pilots, or deals before

Comfortable operating without a playbook in a new org or startup environment

Nice to Have

Robotics, autonomous vehicles, or physical AI experience from a lab, graduate program, or industry team

An existing network among robotics and AI researchers

3+ years in product, solutions, consulting, or another customer-facing role at a startup or high-growth company

Experience designing evaluations or benchmarks for ML systems