Staff PM: ML Training Workflow & Developer Productivity

General Motors; Warren (MI); Hybrid; USD 135,000 - 245,000; Full time

Benefits offered by this job

Bonus potential

Company vehicle program

Job summary

General Motors in Warren, MI is seeking a Staff Product Manager to define and drive product strategy for AI/ML training workflows across GM’s autonomous platform. You will partner with ML engineers, data scientists, and infrastructure teams to shape requirements and prioritize investments.

You’ll measure success with KPIs on developer productivity, training throughput, and cost efficiency, while mentoring other PMs and communicating tradeoffs to senior leadership in a fast-moving, highly

Qualifications

• 8+ years of product management or related technical product experience.
• Experience building products for AI/ML, data science, developer productivity, infrastructure, platform engineering or other highly technical users.
• Proven ability to define product vision, strategy, requirements and success metrics for complex software products from concept through delivery and iteration.
• Strong understanding of the ML lifecycle, including data pipelines, model training, experimentation, evaluation, performance analysis and production handoffs.
• Strong analytical skills with the ability to use quantitative and qualitative evidence to identify workflow bottlenecks, prioritize investments and measure product impact.
• Technical proficiency in working with complex software systems, distributed workflows, cloud or compute infrastructure, and data-intensive products. You must be able to independently reason for distributed training failures, like checkpoint recovery, GPU utilization loss, job variance, orchestration failures and hold a reasonably technical debate with an ML engineer.
• Excellent written and verbal communication skills, including the ability to explain technical concepts, tradeoffs and recommendations to both technical and non-technical partners.
• Demonstrated ability to partner with and influence senior stakeholders and cross‑functional teams without direct reporting authority.
• Comfort operating in ambiguous, fast‑moving technical environments and making clear tradeoffs across speed, quality, cost, reliability and user experience.
• High ownership, resilience and curiosity, with a track record of turning complex customer and engineering problems into practical product outcomes.

Responsibilities

• Own product roadmap and execution for AI/ML training workflow capabilities that improve model development speed, training reliability, experiment traceability and developer productivity.
• Deeply understand the end-to-end ML training lifecycle, including data selection, dataset preparation, training job configuration, orchestration, monitoring, evaluation, debugging and deployment handoffs.
• Act as the voice of ML engineers, data scientists, autonomy developers and infrastructure users by creating and running pain point intake loop, identifying workflow friction, productivity bottlenecks and opportunities to reduce cycle time. Own framework to stack-rank and convert them into prioritized product requirements.
• Define product requirements for training platforms, developer tools, observability systems, workflow automation, experiment management and performance reporting.
• Drive a metrics-based approach to product decisions by defining KPIs for developer productivity, training throughput, cost efficiency, experiment success rates and time-to-insight.
• Prioritize product investments by balancing customer impact, engineering complexity, infrastructure cost, model quality impact and business urgency.
• Fund unglamorous reliability and platform tech debt against competing demand for visible features, and of articulating that tradeoff to senior leaders in terms of throughput and cost beyond engineering hygiene.
• Collaborate with engineering, program management, design, data platform, compute infrastructure and finance teams to deliver high-impact capabilities on predictable timelines.
• Use data, user research, workflow analysis and internal benchmarking to inform roadmap decisions and validate whether shipped capabilities improve developer experience and productivity.
• Communicate product status, tradeoffs, risks and recommendations clearly to senior leaders, technical stakeholders and cross-functional partners.
• Mentor other product managers and cross-functional partners through technical product best practices, without direct people-management responsibility.
• Stay current on AI/ML platform trends, developer productivity tooling, model training infrastructure and competitive approaches to large-scale ML operations.

Skills

PM experience

AI/ML product

Data-driven decisions

Stakeholder influence

Technical proficiency

Communication skills

Lifecycle understanding

Team collaboration

Education

Master’s or PhD in CS/Engineering/Data Science

Job description

General Motors in Warren, MI is seeking a Staff Product Manager to define and drive product strategy for AI/ML training workflows across GM’s autonomous platform. You will partner with ML engineers, data scientists, and infrastructure teams to shape requirements and prioritize investments.

You’ll measure success with KPIs on developer productivity, training throughput, and cost efficiency, while mentoring other PMs and communicating tradeoffs to senior leadership in a fast-moving, highly