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Data Collection Program Manager, Robotics

Mexico, Mexico City · Job Posted February 20, 2026
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Job Description

Scale AI is seeking a hands-on Data Collection Program Manager to own and optimize contributor-facing workflows across hardware, rigs, and physical logistics. This role blends program management, operational problem-solving, and process ownership to ensure smooth execution of complex, work stream projects. You’ll coordinate contributors, manage hardware and rig logistics, and improve SOPs while solving real-world challenges at the intersection of digital and physical workflows. This role is ideal for someone who thrives in operationally complex environments and wants ownership over end-to-end execution.

Job Responsibility

  • Coordinate contributors across multiple operational workflows (no direct reports)
  • Manage hardware and rig logistics to ensure timely, accurate delivery and setup
  • Own SOPs and operational processes, continuously iterating to improve efficiency
  • Solve hands-on problems spanning both digital and physical workflows
  • Track workstreams, identify bottlenecks, and proactively implement solutions
  • Collaborate with cross-functional teams (Engineering, Product, Procurement, Data) to ensure seamless execution
  • Build reporting and feedback loops to provide transparency and inform leadership decisions

Requirements

  • 3–5+ years as a strong Operations or Program Manager with exposure to hardware, logistics, or physical workflows
  • Experience coordinating multiple work streams simultaneously
  • Hands-on problem solver with a bias toward action
  • Comfortable working in a contributor-facing, on-site operational environment
  • Strong organizational skills with the ability to design scalable processes
  • Experience improving processes and SOPs for operational efficiency

Nice to have

  • Experience in hardware operations, rig setup, or warehouse/logistics environments
  • Familiarity with workflow or project management tools
  • Exposure to cross-functional collaboration across engineering, product, or operations teams
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