Skip to content
Physical Intelligence

Annotations Portfolio Lead

San FranciscoOnsite · United States
Staff · FullTime · Operations
POSTED 4 OCTVERIFIED 2H AGO
Apply Ask
Role
36 days opentrue age
Posted 4 Oct
Pay
$177k–$250kno pay posted
Market p25–p75
$177k–$250k
SF Bay Area · n=789 · 365d to 6 Nov
CompanyPhysical Intelligence →
44open roles
Opened · 30d
+1
Closed · 30d
−1
3d of snapshots · 30d window
Market
23,215open · Staff Other
Opened · 7d
+1,5537% of open
All other
623,727open
All tracked boards · live 10 Nov · n=23,215
Visa
5H-1B LCAs · FY26
Median wage
$245k
LCAs FY26 · n=5 · to 2026-05-26

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

Source · Physical IntelligenceFirst seen 2 NovOriginal ↗