Industrial Partnerships Lead, Physical AI

This role mixes industrial partnerships with hands-on data ops. You'll open doors into factories and similar environments, then run the workforce, QA, and platform work that turns that access into reliable multimodal data for frontier labs. Sieve is a multimodal lab curating the world's highest-quality training datasets, spanning video, audio, images, text, and 3D. All roles at Sieve require you to be onsite in San Francisco 5 days per week.

Responsibilities

Identify, pitch, and close partnerships with factories, manufacturers, and industrial operators; navigate security and compliance from first intro through live collection; Run workforce management, task assignment, and QA workflows; build SOPs and training so quality meets frontier lab requirements; Source, onboard, and manage a distributed workforce for annotation, curation, and review; test acquisition and sourcing channels that scale; Ship tooling improvements, track operational metrics, and close gaps in the data platform; Document playbooks so partner wins and ops workflows repeat across sites and programs

Requirements

Direct relationships into factories, manufacturing, or adjacent industrial environments, or a clear track record of building them; Mixed technical and non-technical skillset, comfortable with data tooling, light scripting, and spreadsheet-level analysis; Strong organizational skills and attention to detail, able to manage multiple concurrent work streams; Growth mindset with experience running or contributing to user acquisition, sourcing campaigns, or platform growth; Comfort with ambiguous, relationship-heavy work and the unglamorous ops needed to make a partnership live; Bachelor's in CS, STEM, or equivalent practical experience; in-person at SF HQ

Nice to have

Experience managing human-in-the-loop data operations or annotation pipelines; At least 1 year of engineering experience or strong technical fluency; Prior work inside manufacturing, robotics deployment, factory ops, PE portfolio ops, or as an early hire / AI-lab ops lead; Familiarity with data quality frameworks, ML data pipelines, or physical AI

Benefits

401(k) and full health insurance; Breakfast, lunch, and dinner covered, plus your choice of snacks; Ubers covered home