Staff Product Manager, Synthetic Data for Autonomy

General Motors; Warren (MI); Hybrid; USD 150,000 - 230,000; Full time

Job summary

General Motors is seeking a Staff Product Manager for Synthetic Data to define and execute the strategy and roadmap for trust in synthetic data used in GM’s autonomy training workflow. You will lead cross-functional efforts across Simulation, ML infrastructure and autonomy development to scale synthetic data production and insights.

You’ll navigate ambiguity, make principled tradeoffs, and influence engineers, product, and operations teams through clear narrative and data-driven decision making.

Qualifications

• 5+ years product management experience.
• Bachelor's degree in Engineering or related fields.
• Solid understanding of Simulation platforms, ML orchestration infrastructure and validation workflows.
• Ability to navigate ambiguity and drive projects forward.
• Strong sense of accountability and ownership.
• Proven ability to balance tradeoffs between user needs, technical constraints and business objectives.
• Demonstrated ability to write and narrate complex technical concepts clearly.

Responsibilities

• Own the long-term product vision and strategic direction for Synthetic Data within GM’s training workflow.
• Communicate technically complex information clearly to stakeholders across GM.
• Drive a data-driven culture with KPIs and metrics to measure impact.
• Establish quality frameworks and “is this good enough?” criteria.
• Define and track KPIs showing synthetic data impact on model performance and program outcomes.

Skills

Product management experience

Ambiguity navigation

Data-driven decision making

Education

Bachelor's degree in Engineering or related fields

MBA or master's degree (technical/engineering)

Job description

General Motors is seeking a Staff Product Manager for Synthetic Data to define and execute the strategy and roadmap for trust in synthetic data used in GM’s autonomy training workflow. You will lead cross-functional efforts across Simulation, ML infrastructure and autonomy development to scale synthetic data production and insights.

You’ll navigate ambiguity, make principled tradeoffs, and influence engineers, product, and operations teams through clear narrative and data-driven decision making.