Staff Product Manager, Physical AI Data & Robotics

Scale AI•San Francisco, CA

1d•$240,000 - $300,000•Hybrid

About The Position

Scale is seeking an AI Product Manager to lead the Robotics vertical within its Physical AI team. This role involves owning the development of data and training environments for robots, including teleoperated demonstrations, real-world data collection, simulated tasks, and annotation products. The Product Manager will also be responsible for the "data as a product" strategy that supports these environments. The ideal candidate will have a deep understanding of robotics and physical AI research, be able to identify successful and failing robot policies in real-world workflows, and translate this expertise into valuable datasets, environments, and evaluation frameworks. A strong entrepreneurial and go-to-market mindset is essential for this role.

Requirements

4+ years of direct experience in robotics or physical AI in one or more of: robot learning or manipulation research, teleoperation and data collection systems, robotics software or hardware engineering, or a robotics product role, with real depth in how the work gets done.
Physical AI Fluency: Immersed in current physical AI research — robot policies, vision-language-action models, language-conditioned imitation learning — and able to articulate how the field is moving, not just how classical robotics works.
A builder's mindset: excited by ambiguity and motivated to create new products from the ground up.
Product or customer-facing experience: A track record of owning outcomes, shaping roadmaps, or working closely with technical stakeholders (formal PM experience is a plus but not required if domain depth is strong).
ML Intuition & Technical Fluency: Enough intuition around how model training and evaluation works, and what makes a dataset or environment actually useful for training. A software background is a plus.
Operational rigor: Comfort going deep with Ops on quality and throughput, and reasoning about unit economics across hardware, labor, and annotation cost.
Bias for action: Comfort wearing multiple hats and operating in fast-moving environments.
A degree in Robotics or a related quantitative field (Computer Science, Mechanical Engineering, Electrical Engineering, etc.).

Nice To Haves

Ph.D. in Robotics or a related quantitative field, OR a Master's degree with 3+ years of equivalent professional experience in an applied research setting.

Responsibilities

Own the Robotics AI roadmap & data strategy: Set product direction for the robotics training stack and the data strategy behind it — what data we collect, on which hardware and embodiments, and what we source internally vs. through our marketplace. Establish a vision for where physical AI is heading, driving execution across engineering, operations, and go-to-market teams.
Build partnerships with research teams at frontier labs: Work directly with researchers at leading physical AI labs to understand where their robot policies fall short and shape new product lines and competitive strategy for the vertical. Connect with robotics startups and industry leaders to launch joint benchmarks and build Scale's brand in physical AI.
Design and scale robotics data products and environments: Scope and deliver high-quality collection pipelines, annotation tooling, simulated tasks, and evaluation frameworks — spanning robot-based collection (humanoids and robotic arms performing real-world tasks) and robot-less collection (wearable cameras capturing human demonstrations). Partner with ML and Operations to translate research needs into training products that hit quality, throughput, and cost targets.
Collaborate cross-functionally — influence business priorities and dive into the weeds of research, operations, and customer interactions to deliver mission-critical outcomes. Travel ~10–15% to meet customers, attend conferences, and visit our global data operations.