Senior AI/ML Capacity and Performance Engineer

General Motors (GM)

Hybrid

Quick summary

Work type: Hybrid
Location: Sunnyvale, CA · Seattle, WA
Salary: $144,700–$261,300 / yr
Posted: 62 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $216k

This role $203k

$131k most similar roles pay here $277k

This role pays less than 67% of similar roles. Most pay $186,200–$246,150 — the shaded band above. At the midpoint, this role pays about $203k versus about $216k for comparable roles.

Based on 240 similar postings.

Employer

About General Motors (GM)

General Motors (GM) is a leading American multinational automotive corporation founded in 1908 and headquartered in Detroit, Michigan.

General Motors (GM) currently has 126 open roles on FindRole.

Listed pay typically runs $170,000–$258,500 across 75 roles with salary data.

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At a glance

TL;DR · Senior AI/ML Capacity and Performance Engineer

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GM is seeking a Senior Performance Engineer to join the AV Capacity and Performance Engineering team within the AV Infrastructure organization. This role involves strategic infrastructure development for long-term GPU system strategy, performance optimization through deep analysis of production workloads, cross-functional collaboration with AI/ML Research and Cloud Vendors, and proactive system scaling to enhance engineering velocity and cost-efficiency. The ideal candidate has expert-level Python coding skills, proficiency in PyTorch, hands-on experience with Kubernetes, and technical expertise with Nvidia DCGM, nvidia-smi, and Grafana for GPU monitoring. Additionally, the role requires extensive knowledge of AWS, GCP, or Azure cloud platforms, advanced experience in deploying open-source models via Hugging Face, and proficiency in BigQuery for data analytics. The candidate should also have a deep understanding of distributed systems and high-performance computing (HPC) architectures, including Nvidia's latest GPU technologies like the H100, B200, and GB200.

Skills

Python PyTorch Kubernetes Nvidia DCGM nvidia-smi Grafana AWS GCP Azure H100 B200 GB200 Hugging Face BigQuery Nvidia Nsight Nsight Compute

What you'll do

Conduct deep-dive analyses to identify and resolve bottlenecks in production workloads.
Develop strategic GPU system plans for long-term infrastructure scalability.
Collaborate with cross-functional teams to enhance engineering velocity and cost-efficiency.
Architect improvements to ensure the reliability of large-scale ML training environments.
Utilize Nvidia DCGM, nvidia-smi, and Grafana for real-time monitoring and observability.
Provide capacity planning expertise to support GM’s autonomous vehicle development efforts.

What we're looking for

5+ years of professional experience in high-scale infrastructure or ML systems.
Bachelor’s Degree in Computer Science or related technical field.
Expert-level coding skills in Python and PyTorch ecosystem.
Proven track record resolving performance issues in large-scale distributed environments.
Deep understanding of modern ML system design and HPC, hands-on Kubernetes experience.
Technical proficiency with Nvidia DCGM, nvidia-smi, and Grafana for GPU monitoring.
Extensive experience working within major cloud ecosystems (AWS, GCP, or Azure).

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