Hands-on technical background in engineering or research.
Prior work with researchers on pre-training or post-training data at a lab, model company, or data vendor.
Fluency in how robot learning models are trained and evaluated, including imitation learning, world models, and vision-language-action-style policies.
Experience scoping and landing external projects, pilots, or deals.
Comfort operating without a playbook in a new organization or startup environment.
Responsibilities
Build trusted relationships with researchers and stakeholders who control spend at frontier robotics and embodied AI labs, and serve as their technical point of contact.
Advise customers on robotics data for pre-training and post-training, including egocentric video, teleoperation, tactile capture, and model evaluation.
Run the benchmark and publication roadmap with the research team.
Co-design pilot prototypes and define requirements with researchers across task and environment mix, capture configuration, annotation and quality-control criteria, delivery format, and success metrics.
Work hands-on with data in the robotics lab by inspecting early samples, playing back data on robotics, and conducting quality evaluations.
Capture forward demand by predicting what labs will need in 6–12 months and feeding it into the company roadmap.
Desired Qualifications
Robotics, autonomous vehicles, or physical AI experience from a lab, graduate program, or industry team.
An existing network among robotics and AI researchers.
At least 3 years in product, solutions, consulting, or another customer-facing role at a startup or high-growth company.
Experience designing evaluations or benchmarks for machine-learning systems.
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