Senior AI/ML Performance Engineer
AI summary of the role
GM's AV Infrastructure org seeks a Senior Performance Engineer to join the AV Capacity and Performance Engineering team, responsible for shaping ML infrastructure strategy, optimizing GPU workloads, and managing cloud budgets for autonomous vehicle development.
No longer in the current catalog. Last included 2026-09-09. Check the employer’s posting for availability.
What you’ll do
- Adopt and run AV models to support GM's long-term GPU system strategy and evergreen infrastructure roadmap.
- Conduct deep-dive analyses of production workloads to identify bottlenecks and propose high-impact optimization strategies.
- Partner with AI/ML Research, Infrastructure Engineering, and Cloud Vendors to spearhead projects that enhance engineering velocity and cost-efficiency.
- Identify opportunities for architectural improvements to ensure the scalability and reliability of large-scale ML training and inference environments.
What you’ll bring
- 5+ years of professional experience in high-scale infrastructure or ML systems.
- Expert-level coding skills in Python and ability to architect/debug within the PyTorch ecosystem.
- Proven track record of resolving performance issues within large-scale distributed production environments.
- Deep understanding of distributed systems, specifically modern ML system design and high-performance computing (HPC).
Technologies
Python · PyTorch · Kubernetes · Nvidia DCGM · nvidia-smi · Grafana · AWS · GCP · Azure · Hugging Face · BigQuery · Nvidia Nsight
About General Motors
Global automaker selling Chevrolet, GMC, Cadillac, and Buick vehicles, plus financing and connected services, while shifting into EVs and driver assistance.
Public · 5000+ people
Source and classification
Internal deployment & tooling · Evidence for this classification:
Job Description About Us: The AV Infrastructure org provides developer environments, cloud infrastructure, and ML/AI GPU platforms for AV research and development teams to build, test, and run faster in GM. The Role: GM is looking for a Senior Performance Engineer to join the AV Capacity and Performance Engineering team in the AV Infrastructure org to support our critical efforts in developing autonomous vehicles. The mission of the AVCPE team is to provide input into large scale ML infrastructure strategy, advise on key decisions affecting our cloud budget, identify and execute optimization projects, and provide capacity planning and engineering expertise to support GM’s efforts in developing autonomous vehicles (AV). What you’ll be doing (Responsibilities) Strategic Infrastructure Development: Adopt and run AV models to support GM’s long-term GPU system strategy and "evergreen"
More from the job description
Job Description About Us: The AV Infrastructure org provides developer environments, cloud infrastructure, and ML/AI GPU platforms for AV research and development teams to build, test, and run faster in GM. The Role: GM is looking for a Senior Performance Engineer to join the AV Capacity and Performance Engineering team in the AV Infrastructure org to support our critical efforts in developing autonomous vehicles. The mission of the AVCPE team is to provide input into large scale ML infrastructure strategy, advise on key decisions affecting our cloud budget, identify and execute optimization projects, and provide capacity planning and engineering expertise to support GM’s efforts in developing autonomous vehicles (AV). What you’ll be doing (Responsibilities) Strategic Infrastructure Development: Adopt and run AV models to support GM’s long-term GPU system strategy and "evergreen" infrastructure roadmap. Performance Optimization: Conduct deep-dive analyses of production workloads to identify bottlenecks and propose high-impact optimization strategies. Cross-Functional Collaboration: Partner with AI/ML Research, Infrastructure Engineering, and Cloud Vendors to spearhead projects that enhance engineering velocity and cost-efficiency. Proactive System Scaling: Identify opportunities for architectural improvements to ensure the scalability and reliability of large-scale ML [... source excerpt omitted ...] in Python and the ability to architect/debug within the PyTorch ecosystem. Systems Engineering: Proven track record of resolving performance issues within large-scale distributed production environments. Architectural Knowledge: Deep understanding of distributed systems, specifically modern ML system design and high-performance computing (HPC). Containerization: Hands-on experience with Kubernetes for orchestrating complex workloads. GPU Monitoring: Technical proficiency with Nvidia DCGM, nvidia-smi, and Grafana for real-time telemetry and observability. Cloud Platforms: Extensive experience working within major cloud ecosystems (AWS, GCP, or Azure). What will give you a comp [... source excerpt omitted ...] nce programs, employee assistance program, GM vehicle discounts and more. 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 make our world better, safer and more equitable for all. Why Join Us We believe we all must make a choice every day – individually and collectively – to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team. Benefits Overview From day one, we're looking out for your well-being–at work and at home–so you can focus on realizing your ambitions. Learn how GM supports a
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