Senior Product Manager, Labeling

General Motors Australia & New Zealand

Warren, MI, USA
Base: $106,600 to $192,700; bonus/equity: incentiv...
Hybrid
Product vision for labeling ecosystem
Ui and workflow requirements for labeling tools
Strategy for automatic and semi-automatic labeling
Define and drive the product vision for GM’s labeling ecosystem, spanning UI tools for human annotation, workflow and efficiency optimization, and strategy for automatic and semi‑automatic labeling solutions

Job Summary

  • Define and drive the product vision for GM’s labeling ecosystem, spanning UI tools for human annotation, workflow and efficiency optimization, and strategy for automatic and semi‑automatic labeling solutions.
  • Partner closely with machine learning teams across AV and ADAS to understand their data and model‑training needs, ensuring labeling quality, throughput, and cost‑efficiency scale with the demands of next‑generation perception and planning systems.
  • GM offers a variety of health and wellbeing benefit programs, including medical, dental, vision, retirement savings plan, and more.

Matching Summary

Define and drive the product vision for GM’s labeling ecosystem, spanning UI tools for human annotation, workflow and efficiency optimization, and strategy for automatic and semi‑automatic labeling solutions.

Salary

Base: $106,600 to $192,700; Bonus/Equity: Incentive pay program based on company, job level, and individual performance; Benefits: Health and wellbeing benefit programs

Skills & Requirements

Must-have

  • product vision for labeling ecosystem
  • UI and workflow requirements for labeling tools
  • strategy for automatic and semi-automatic labeling
  • understand ML customer needs
  • balance quality and velocity for ML customers
  • drive efficiency investments for human labelers
  • establish labeling KPIs

Nice-to-have

  • experience in robotics
  • background in ML or computer vision
  • familiarity with annotation platforms

Key Requirements

  • 5+ years product management experience
  • translate ML customer needs into requirements
  • define workflow and UI requirements
  • balance annotation quality, throughput, cost, ML impact
  • strong written communication skills
  • identify and instrument key metrics
  • work across engineering, operations, research teams

Work Rights

Not specified

Tailored Resume

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