Staff Technical Program Manager, AI Infrastructure

About the Role

We are seeking a Staff Technical Program Manager (TPM) to lead AV ML Infrastructure programs for our autonomous driving platform. In this role, you will own strategy and execution for large-scale ML infrastructure – including training pipelines, model lifecycle management, compute orchestration, and platform reliability – that power next-generation autonomy models. You will operate at the intersection of ML engineering, platform infrastructure, and operations, ensuring our systems are scalable, efficient, and production-ready to support end-to-end model development at scale.

Responsibilities

• Program Leadership: Own end-to-end delivery of ML infrastructure programs, driving measurable improvements in training throughput, platform reliability, and developer productivity. Establish clear goals, milestones, and success metrics across teams.
• Cross-Functional Alignment: Partner with ML engineers, platform teams, validation, and product to prioritize initiatives, drive tradeoff decisions, and accelerate the AI development lifecycle.
• Technical Roadmapping: Translate complex MLOps challenges – distributed training orchestration, compute scheduling, pipeline scaling – into clear, actionable plans with defined ownership and outcomes.
• Scalability & Reliability: Drive infrastructure evolution to support growing model complexity, dataset scale, and compute demand, with a strong focus on resiliency, observability, and performance.
• Risk & Dependency Management: Identify risks early, manage cross-team dependencies, and implement mitigation strategies to ensure stable, predictable delivery.
• Operational Excellence: Establish best practices for monitoring, incident response, and capacity planning to ensure high system uptime and efficient resource utilization.
• Metrics & Visibility: Define and track KPIs (e.g., system reliability, utilization, training cycle time), delivering clear, executive-ready insights on program health and progress.

Requirements

• 10+ years of technical program management experience leading large, complex, cross-functional initiatives.
• 5+ years working in ML infrastructure, MLOps, AI platform engineering, or distributed compute environments.
• BS or MS in Engineering, Computer Science, or a related technical field.
• Experience delivering large-scale ML infrastructure programs, including compute orchestration, pipeline reliability, and resource management.
• Proven ability to lead programs spanning infrastructure, software, and data systems in ambiguous, fast-evolving environments.
• Strong analytical skills with the ability to interpret system metrics and drive performance improvements.
• Excellent communication and stakeholder management skills, with the ability to influence across technical and non-technical audiences.
• Deep familiarity with Agile delivery, JIRA (or similar tools), and technical program reporting frameworks.

Preferred Qualifications

• Experience scaling large-scale ML infrastructure, including GPU compute, cluster orchestration (e.g., Kubernetes, Slurm), or cloud platforms (AWS, GCP, Azure).
• Familiarity with ML workflow orchestration and MLOps tooling (e.g., Kubeflow, Airflow).
• Background in SRE, platform engineering, or DevOps practices applied to distributed ML systems.
• Experience with observability frameworks, SLO/SLI design, and incident management in production environments.

Pay

The salary range for this role is $159,400 - $245,000. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position, as well as geography of the selected candidate. An incentive pay program offers payouts based on company performance, job level, and individual performance.

Benefits

• Medical, dental, and vision insurance.
• Health Savings Account and Flexible Spending Accounts.
• Retirement savings plan.
• Sickness and accident benefits, life insurance.
• Paid vacation and holidays.
• Tuition assistance programs.
• Employee assistance program.
• GM vehicle discounts.
• Company vehicle evaluation program (upon successful completion of a motor vehicle report review).

Schedule

This role is based remotely, but if the selected candidate lives within a specific mile radius of a GM hub, they will be expected to report to the location three times a week (or other frequency dictated by your manager). This job may be eligible for relocation benefits.