Senior AI/ML Performance Engineer

General Motors (GM)

Confirmed live today High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Sunnyvale, CASeattle, WA
Salary
$144,700–$261,300 / yr
Employment
Full-time
Posted
21 days ago
Freshness
Confirmed live today

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $207k
This role $203k
$131k $275k
below market most similar roles pay here above market

This role pays less than 52% of similar roles. Most pay $171,637–$241,750 — the blue band above. At the midpoint, this role pays about $203k versus about $207k 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 196 open roles on FindRole.

Listed pay typically runs $159,200–$245,000 across 54 roles with salary data.

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View all roles at General Motors (GM)

At a glance

TL;DR · Senior AI/ML Performance Engineer

The Senior AI/ML Performance Engineer joins the AV Capacity and Performance Engineering team within the AV Infrastructure organization. This role focuses on supporting the development of autonomous vehicles by providing input into large-scale ML infrastructure strategy and capacity planning. You will conduct deep-dive analyses of production workloads to identify bottlenecks, propose high-impact optimization strategies, and execute projects to enhance engineering velocity and cost-efficiency. Key responsibilities include adopting AV models to support long-term GPU system strategies and ensuring the scalability of training and inference environments. Required technical skills include expert-level Python coding, PyTorch ecosystem debugging, and experience with Kubernetes, distributed systems, and high-performance computing. You will utilize tools such as Nvidia DCGM, nvidia-smi, Grafana, BigQuery, and Nvidia Nsight for real-time telemetry, data analysis, and kernel-level performance tuning.

What you'll do

  • Adopt and run AV models to support long-term GPU system strategy and infrastructure roadmaps.
  • Conduct deep-dive analyses of production workloads to identify and resolve performance bottlenecks.
  • Propose and execute high-impact optimization strategies for large-scale ML training and inference environments.
  • Provide capacity planning and engineering expertise to support autonomous vehicle development.
  • Identify architectural improvements to ensure the scalability and reliability of distributed production systems.
  • Advise on key decisions affecting the cloud budget and large-scale ML infrastructure strategy.
  • Spearhead projects with AI/ML Research and Cloud Vendors to enhance engineering velocity and cost-efficiency.

What we're looking for

  • 5+ years of professional experience in high-scale infrastructure or ML systems.
  • Bachelor’s Degree in Computer Science, a related technical field, or equivalent practical experience.
  • Expert-level coding skills in Python and the 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).
  • Hands-on experience with Kubernetes for orchestrating complex workloads.
  • Technical proficiency with Nvidia DCGM, nvidia-smi, and Grafana for real-time telemetry and observability.
  • Extensive experience working within major cloud ecosystems (AWS, GCP, or Azure).

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