Senior ML Compiler Engineer

General Motors (GM)

Hybrid

Quick summary

Work type
Hybrid
Location
Sunnyvale, CA · Washington · Austin, TX · San Francisco, CA · Warren, MI
Salary
$128,700–$261,300 / yr
Posted
4 days ago

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $187k
This role $195k
$113k most similar roles pay here $277k

This role pays more than 52% of similar roles. Most pay $148,375–$225,440 — the shaded band above. At the midpoint, this role pays about $195k versus about $187k 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.

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View all roles at General Motors (GM)

At a glance

TL;DR · Senior ML Compiler Engineer

As a Senior Compiler Engineer on GM’s AI Kernels & Compilers team, you will work on the cutting-edge model compilation pipeline that transforms high-level models into optimized inference engines for autonomous and assisted driving systems. Your responsibilities include building new compiler passes to enhance build times, memory efficiency, and runtime performance while adhering to strict safety standards. You’ll collaborate closely with hardware and software teams to design interfaces and optimize accelerator capabilities, ensuring the compiler exposes optimal abstractions for peak performance. Additionally, you will establish best practices for model export and validation to enable rapid iteration within GM’s AV organization. The role requires expertise in ML frameworks like PyTorch or TensorFlow, proficiency in Python/C++, and experience with ONNX, MLIR, and CUDA programming. This position offers the opportunity to work on real-world autonomy challenges at a leading automotive company.

What you'll do

  • Build and evolve the model compilation toolchain for deploying large-scale perception, prediction, and planning models.
  • Architect new compiler passes to optimize build times, memory footprint, and runtime latency under strict safety constraints.
  • Collaborate with hardware teams to design interfaces that unlock peak performance on each platform.
  • Set standards and best practices for model export, validation, and debugging to ensure quick iteration by AV teams.
  • Develop robust tooling to validate numerical correctness and detect performance regressions in the compilation pipeline.

What we're looking for

  • 3+ years of experience in compilers
  • Expertise in ML frameworks (PyTorch, TensorFlow, JAX) and software stack (ONNX, MLIR, XLA)
  • Proficiency in writing production-quality Python/C++ code
  • Strong background in the software development lifecycle including coding, debugging, optimization, testing, and integration
  • BS or higher degree in CS/CE/EE or equivalent
  • Experience with GPU programming (CUDA) and familiarity with ML SW stack components like cuDNN, cuBLAS

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