Staff Machine Learning Engineer, Compute

General Motors (GM)

Remote

Quick summary

Work type
Remote
Location
Remote
Salary
$198,900–$304,800 / yr
Posted
98 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $217k
This role $252k
$156k most similar roles pay here $321k

This role pays more than 78% of similar roles. Most pay $183,733–$249,750 — the shaded band above. At the midpoint, this role pays about $252k versus about $217k 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.

Most-posted roles

View all roles at General Motors (GM)

At a glance

TL;DR · Staff Machine Learning Engineer, Compute

As a Staff ML Engineer on the ML Compute Platform team within Infrastructure Platforms at GM, you will play a pivotal role in scaling and optimizing our cloud-agnostic AI infrastructure for autonomous vehicles and other AI-driven products. Your responsibilities include designing core backend software components, integrating with GPU hardware and orchestration systems, and enhancing system architecture and user experience. You’ll work with technologies like Kubernetes, Go, C++, Python, and cloud platforms such as GCP and Azure to ensure high performance, reliability, and scalability. Ideal candidates have a strong background in distributed systems, at least 7 years of industry experience, and hands-on expertise in large-scale infrastructure projects. Experience with ML frameworks like PyTorch and GPU optimizations is preferred, making this role ideal for those passionate about shaping the future of AI infrastructure.

What you'll do

  • Design core backend software components for the ML Compute Platform.
  • Optimize efficiency and scalability of system resources across platforms.
  • Integrate GPU hardware and orchestration systems to enhance performance.
  • Drive large-scale initiatives to improve the GM ML ecosystem.
  • Collaborate with cross-functional teams to incorporate innovative solutions.

What we're looking for

  • 7+ years of industry experience in software engineering or related field
  • Expertise in Go, C++, Python, Kubernetes, and distributed systems
  • Experience leading large-scale initiatives and driving system improvements
  • Strong background in cloud platforms like GCP, Azure, or AWS
  • Hands-on experience with GPU/TPU optimizations and ML training frameworks
  • Proven ability to work effectively in a dynamic, multi-tasking environment

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