Annotations Portfolio Lead at Physical Intelligence (San Francisco, CA)
Physical Intelligence· San Francisco, CA·
Role details
Job description
Who We Are
Physical Intelligence is bringing general-purpose AI into the physical world. We are a group of engineers, scientists, roboticists, and company builders developing foundation models and learning algorithms to power the robots of today and the physically-actuated devices of the future.
The Team High-quality data is the fuel for our work. The Annotations team produces high-quality data labels to support model development. This role is a hands-on owner for a portfolio of annotation programs: partnering with researchers to understand what data they need and why, translating that into concrete requirements and rubrics, and running the operation that delivers the data. This person will also be expected to drive continuous improvement across multiple surfaces to mature the annotations function and balance strategic problem solving with tactical execution. In this role you will
- Own end-to-end performance for a portfolio of annotation programs, driving quality, speed, and efficiency
- Partner with researchers to define and refine requirements
- Drive step-function continuous improvement in our operations, identifying issues and building scalable solutions
- Foster clarity, collaboration, and alignment across both technical and nontechnical stakeholders, including vendor partners, researchers, operations
What we hope you'll bring
- 5+ years of experience in program management, operations, technical project management, consulting, startup operations, or similar roles
- Strong problem solving and systems thinking; ability to identify points of leverage in a constantly-evolving system and diagnose problems with incomplete information
- Intuition for data quality and research needs, grounded in understanding of model training and evaluation
- Stellar communication and ability to clarify nuance, structure complex information in digestible ways, and work with remote, ESL audiences
- Organizational skills to bring structure to chaos and balance needs across multiple programs
Bonus points
- Experience with data annotations for ML/AI, having seen versions of this problem before
- Experience with robotics, egocentric video, or other multimodal sensor data
- Experience with using coding agents to fill gaps in tooling / infra
Why work at Physical Intelligence
- Culture: Described as a “pure company” – internally driven by research needs, not external market demands. Highly collaborative, with a mix of engineers, scientists, and roboticists working together.
- Work Environment: Hybrid/in-office – most roles require on-site presence in San Francisco (396 Treat Ave), though some remote flexibility exists. In-office setting with a “no reception” vibe, open lab space with robot stations.
- Growth: Team has scaled from ~80 (Jan 2026) to 163 (mid-2026) and is still hiring across research, ML infra, hardware, and engineering roles. Plans to grow “as slowly as possible” to maintain quality.
- Perks & Engineering Highlights: Access to cutting-edge robotics hardware and compute resources; opportunity to publish research and open-source code; exposure to a wide variety of real-world automation challenges (e.g., robots learning to fold pants, peel vegetables, make espresso). Employees come from top institutions like Berkeley, Stanford, Google, NVIDIA, and Anduril.