Senior ML Engineer, ML compute

General Motors (GM)

Hybrid

Quick summary

Work type
Hybrid
Location
Mountain View, California
Salary
$155,420–$395,900 / yr
Posted
109 days ago
Nearby
99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $211k
This role $276k
$127k most similar roles pay here $425k

This role pays more than 91% of similar roles. Most pay $176,000–$246,150 — the shaded band above. At the midpoint, this role pays about $276k versus about $211k for comparable roles.

Based on 239 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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View all roles at General Motors (GM)

At a glance

TL;DR · Senior ML Engineer, ML compute

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As a Senior Software Engineer on the ML Compute Platform team within Infrastructure Platforms at General Motors, you will play a pivotal role in scaling our AI infrastructure platform for performance, reliability, and usability. Your responsibilities include designing core backend software components, integrating with GPU hardware and orchestration systems, and enhancing system architecture and user experience. You will work closely with other teams to incorporate their innovations while analyzing and improving the efficiency, scalability, and stability of various system resources. The role requires expertise in distributed systems, infrastructure, and cloud platforms like GCP or Azure, as well as hands-on experience with Kubernetes at scale and ML frameworks such as PyTorch and Ray. You should have a strong background in Go, C++, Python, or similar languages and be adept at leading large-scale initiatives within the GM ML ecosystem.

Skills

Python Kubernetes Go C++ GCP Azure AWS PyTorch TorchX Ray Docker CI/CD

What you'll do

  • Design and develop core backend software components for the ML compute platform.
  • Optimize GPU utilization across different hardware platforms for efficiency.
  • Analyze system performance to enhance scalability, stability, and reliability.
  • Integrate with cloud orchestration systems like Kubernetes at scale.
  • Drive large-scale initiatives to improve the GM ML ecosystem’s infrastructure.
  • Collaborate with cross-functional teams to incorporate new innovations and technologies.

What we're looking for

  • 5+ years of industry experience in software engineering.
  • Expertise in Go, C++, Python or relevant coding languages.
  • Strong background with Kubernetes at scale and distributed systems.
  • Experience leading large-scale initiatives and working on cloud platforms (GCP, Azure).
  • Hands-on experience in ML platforms, GPU/TPU optimizations, and training frameworks like PyTorch.

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