Senior ML Infrastructure Engineer (Compute)

General Motors (GM)

Remote

Quick summary

Work type
Remote
Location
Remote
Posted
11 days ago
Closes
Jun 24, 2026

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Similar $199k
$149k most similar roles pay here $251k

This listing doesn't post a salary. Most similar roles pay $162,000–$235,750.

Based on 240 similar postings.

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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 ML Infrastructure Engineer (Compute)

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As a Senior ML Infrastructure Engineer on GM’s AI Validation Platform team, you will play a pivotal role in building and scaling robust compute platforms for simulation workflows, focusing on high GPU utilization and reliability. Your responsibilities include designing core platform backend software components, collaborating with Simulation engineers to translate critical workflows into technical requirements, and leading decision-making on Compute architecture and auto-scaling mechanisms. You will also drive the development of monitoring tools and metrics to ensure optimal performance and resource efficiency while researching and integrating cutting-edge frameworks and hardware accelerators. Ideal candidates have 4+ years of experience in high-performance backend services with expertise in Go or similar languages, along with a strong background in cloud platforms like GCP, Azure, or AWS. Experience in HPC and hardware-in-the-loop validation systems is preferred, as you will be shaping the future of AI infrastructure at GM by influencing technical leadership and best practices across multi-functional teams.

Skills

Go AWS GCP Azure Docker Kubernetes CI/CD Prometheus Grafana PostgreSQL Redis HPC GPU Telemetry Python C++ REST GraphQL GitLab

What you'll do

  • Design and implement core platform backend software components for AI validation.
  • Lead technical decision-making on Compute architecture and cloud capacity provisioning.
  • Drive development of monitoring, observability, and metrics for reliability and performance.
  • Proactively research and integrate frameworks, hardware accelerators, and distributed computing techniques.
  • Collaborate with Simulation engineers to understand workflows and deliver incremental value.

What we're looking for

  • At least 4 years of industry experience in high-performance backend services.
  • Expertise in Go or similar programming languages.
  • Experience working with cloud platforms like GCP, Azure, or AWS.
  • Strong problem-solving skills and ability to drive cross-functional initiatives.
  • Hands-on experience with Cloud VM services such as Google Compute Engine.
  • Familiarity with hardware acceleration (GPUs) and optimizations.
  • Proven technical leadership in developing scalable distributed systems.

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