Senior ML Infrastructure Engineer, Inference Platform

General Motors (GM)

Hybrid

Quick summary

Work type: Hybrid
Location: Sunnyvale, CA · Austin, TX · Mountain View, CA · Warren
Salary: $155,420–$205,900 / yr
Posted: 11 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $211k

This role $181k

$143k most similar roles pay here $270k

This role pays less than 73% of similar roles. Most pay $174,980–$246,150 — the shaded band above. At the midpoint, this role pays about $181k 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 Infrastructure Engineer, Inference Platform

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As a Senior ML Infrastructure Engineer on the ML Inference Platform team within GM’s AV ML Infrastructure organization, you will design and implement core backend software components for efficient model serving and inference in production. Your day-to-day responsibilities include collaborating with ML engineers to understand critical workflows, leading technical decision-making on model serving strategies, and driving development of monitoring tools to ensure reliability and performance. You will also research and integrate state-of-the-art frameworks and hardware accelerators, contribute to open-source projects, and lead initiatives across GM’s ML ecosystem. The role requires expertise in Python or C++, experience with ML inference frameworks like Triton and RayServe, and a strong background in distributed systems and high-performance backend services. This position offers the opportunity to shape the architecture of a robust ML inference service supporting real-time and batch processing needs for autonomous vehicle development and other AI-driven products at GM.

Skills

Python Triton RayServe vLLM C++ Kubernetes Docker CI/CD Prometheus Grafana PostgreSQL Redis AWS Azure Google Cloud Platform Git Jenkins GitHub Slack Confluence Jira

What you'll do

Design and implement core platform backend software components for ML inference.
Lead technical decision-making on model serving strategies and auto-scaling mechanisms.
Drive development of monitoring, observability, and metrics for inference services reliability.
Proactively research and integrate state-of-the-art model serving frameworks and hardware accelerators.
Raise the engineering bar through technical leadership and best practice establishment.

What we're looking for

5+ years of industry experience in machine learning systems or high-performance backend services.
Expertise in ML inference and model serving frameworks like Triton, RayServe, vLLM.
Proficiency in Python, C++, or relevant coding languages for system development.
Strong communication skills to drive cross-functional technical initiatives effectively.
Experience with distributed systems and large-scale data processing.
Familiarity with hardware acceleration (GPUs) and optimizations for inference workloads.

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