Senior Robotics Data-Collection Strategy Lead

Scale; San Francisco (CA); On-site; USD 152,000 - 228,000; Full time

Benefits offered by this job

Equity compensation

Health, dental and vision coverage

Retirement benefits

Learning and development stipend

Generous PTO

Commuter stipend

Job summary

Scale’s Robotics unit seeks a Senior Strategic Project Lead to architect and execute critical operational roadmaps for egocentric data collection, driving $XXM+ in revenue. This executive-facing role spans operations, engineering strategy, and product, delivering data-engineered solutions for Embodied AI systems.

You will own high-impact programs, translate customer ML requirements into scalable data collection specs, and build global, metric-driven operations with strong governance and risk

Qualifications

• 5+ years of elite project/program management across complex lifecycles.
• Experience driving PMO frameworks and cross-functional technical teams (PMP, Agile/Scrum).
• Physical AI/Robotics exposure or familiarity with robotics systems is a plus.

Responsibilities

• Own end-to-end program for egocentric data collection initiatives, steering data quality and revenue delivery.
• Bridge physical and digital requirements to scalable data collection specs for model performance.
• Establish PMO rigor with timelines, milestones, risk frameworks, and critical-path infrastructure.
• Lead cross-functional governance with Engineering, Product, Finance, and Go-to-Market leaders.

Skills

Project management

PMO frameworks

Cross-functional leadership

Agile/Scrum

Data analytics

Education

Bachelor's degree in Engineering or Computer Science

Tools

SQL

Tableau

Looker

Job description

Scale’s Robotics unit seeks a Senior Strategic Project Lead to architect and execute critical operational roadmaps for egocentric data collection, driving $XXM+ in revenue. This executive-facing role spans operations, engineering strategy, and product, delivering data-engineered solutions for Embodied AI systems.

You will own high-impact programs, translate customer ML requirements into scalable data collection specs, and build global, metric-driven operations with strong governance and risk