Staff Technical Program Manager, AI Infrastructure

About this role

Job Description Staff Technical Program Manager, AI Infrastructure

At General Motors, our product teams are redefining mobility. Through a human-centered design process, we create vehicles and experiences that are designed not just to be seen, but to be felt. We’re turning today’s impossible into tomorrow’s standard – from breakthrough hardware and battery systems to intuitive design, intelligent software, and next-generation safety and entertainment features.

Every day, our products move millions of people as we aim to make driving safer, smarter, and more connected, shaping the future of transportation on a global scale.

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.

What You’ll Do • 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.

Your Skills & Abilities (Required Qualifications) • 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

What will give you a competitive edge (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

Compensation: The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. 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. • 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.

• Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.

• Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.

Company Vehicle: Upon successful completion of a motor vehicle report review, you will be eligible to participate in a company vehicle evaluation program, through which you will be assigned a General Motors vehicle to drive and evaluate. Note: program participants are required to purchase/lease a qualifying GM vehicle every four years unless one of a limited number of exceptions applies. 



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.

 About GM Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will

Similar jobs

• Staff Technical Program Manager, AI — Cribl · Remote
• Technical Program Manager, AI Infrastructure — Character · Remote
• Senior Technical Program Manager, AI Infrastructure and Capacity Operations — NVIDIA · Remote
• Staff Technical Program Manager, AI Native — Life360 · Remote
• Technical Program Manager, AI Delivery — Cohere · United States
• Technical Program Manager - AI & Data Systems — Abnormalsecurity · Remote
• Technical Program Manager (AI/ML) — Cuspai · Berlin, DE
• Senior/Staff Technical Program Manager - Artificial Intelligence — Zoox · Foster City, CA