General Motors

Senior ML Compiler Engineer

General Motors$128K — $261K *
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 3+ years of experience in the field of compilers
  • Experience with ML frameworks (e.g., PyTorch, TensorFlow, JAX) and software stack (e.g., ONNX, MLIR, XLA, TVM, TensorRT, etc)
  • Expertise in writing production quality Python/C++ code
  • Expertise in the software development life-cycle - coding, debugging, optimization, testing, integration
  • BS, or higher degree, in CS/CE/EE, or equivalent

Responsibilities

  • Build and evolve the model compilation toolchain used to deploy large-scale perception, prediction, and planning models to the AV.
  • Architect new compiler passes and analysis to improve build times, memory footprint, and runtime latency while preserving safety and reliability constraints.
  • Collaborate closely with kernels, runtime, and hardware teams to co-design interfaces and ensure optimal performance on each platform.
  • Set standards and best practices for model export, validation, and debugging to enable quick iteration with clear performance characteristics.

Benefits

  • Diverse health and wellbeing benefit programs including medical, dental, vision.
  • Health Savings Account and Flexible Spending Accounts options.
  • Retirement savings plan and life insurance benefits.
  • Paid vacation and holidays.
  • Tuition assistance programs and employee assistance program.
  • GM vehicle discounts and more.
Full Job Description
Job Description

The Role

As a Senior Compiler Engineer on the AI Kernels & Compilers team, you will work on the compilation stack that takes high-level models and turns them into highly optimized inference artifacts running on GM's autonomous and assisted driving platforms. You'll be a key contributor to a pipeline and tooling that makes that path fast, reliable, and effortless for ML engineers across the AV organization to compile their models.

You will work on an evolving a state-of-the-art model export and compilation pipeline-from capturing high-level model graphs, through intermediate representations and compiler transforms, into accelerator-specific inference engines and their integration with our runtime- so that we can simultaneously optimize compilation throughput, model fidelity, and on-vehicle latency. Along the way, you'll build robust tooling to validate numerical correctness, detect and bisect performance regressions, and surface clear, actionable diagnostics back to model authors.

If you want to work at the intersection of compilers, performance engineering, and real-world autonomy, this role puts your decisions directly on the critical path of what runs on the car.

What you'll be doing (Responsibilities)

  • Build and evolve the model compilation toolchain used to deploy large-scale perception, prediction, and planning models to the AV.


  • Architect new compiler passes and analysis that improve build times, memory footprint, and runtime latency while preserving-or intentionally trading off-fidelity under strict safety and reliability constraints.


  • Collaborate closely with kernels, runtime, and hardware teams to co-design interfaces, shape accelerator capabilities, and ensure the compiler exposes the right abstractions to unlock peak performance on each platform.


  • Set standards and best practices for model export, validation, and debugging so that AV teams can iterate quickly with clear, reproducible performance and accuracy characteristics.


Your Skills & Abilities (Required Qualifications)

  • 3+ years of experience in the field of compilers


  • Experience with ML frameworks (e.g., PyTorch, TensorFlow, JAX) and software stack (e.g., ONNX, MLIR, XLA, TVM, TensorRT, etc)


  • Expertise in writing production quality Python/C++ code


  • Expertise in the software development life-cycle - coding, debugging, optimization, testing, integration


  • BS, or higher degree, in CS/CE/EE, or equivalent


What Will Give You A Competitive Edge (Preferred Qualifications)

  • Experience building and optimizing ONNX-based model export and deployment pipelines


  • GPU programming (CUDA) and familiarity with ML SW stack (e.g., cuDNN, cuBLAS)


  • Experience with ML accelerators and hardware architecture


  • Experience developing and deploying machine learning models


Compensation: The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of New York, Colorado, California, or Washington.
  • The salary range for this role: is $128,700 to $261,300. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position.
  • Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.
  • Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.


#GM-AV-1

This role is categorized as hybrid. This means the selected candidate is expected to report to a specific location at least 3 times a week {or other frequency dictated by their manager}.The selected candidate will be required to travel

About General Motors

General Motors Company engages in the manufacture and sale of cars and trucks in the United States, China, Brazil, Germany, the United Kingdom, Canada, and Italy. It offers sedans, crossovers, sport utility vehicles, pick-up trucks, coupes, sports/convertibles and hybrid vehicles, hatchbacks/wagons, and vans, as well as mini cars in India. The company also provides parts and accessories, such as iPod and MP3 compatibility, mobility accessories, performance parts, AC parts and services, and merchandise. In addition, it offers vehicle safety, security, and information services. The company provides used vehicles. It offers its products through dealers and distributors. General Motors Company was formerly known as NGMCO, Inc. and changed its name to General Motors Company in July 2009. The company was incorporated in 2009 and is based in Detroit, Michigan. It operates manufacturing facilities in India, the United States, and Canada. General Motors Company operates as a subsidiary of the United States Department of The Treasury. General Motors led global vehicle sales for 77 consecutive years from 1931 through 2007, longer than any other automaker, and is currently among the world's largest automakers by vehicle unit sales. General Motors acts in most countries outside the USA via wholly-owned subsidiaries but operates in China through 10 joint ventures. GM's OnStar subsidiary provides vehicle safety, security, and information services. In 2009, General Motors shed several brands, closing Saturn, Pontiac, and Hummer, and emerged from a government-backed Chapter 11 reorganization. In 2010, GM made an initial public offering IPOs to date and returned to profitability later that year.

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Join the dynamic team at General Motors, a global leader in automotive innovation and technology. At General Motors, we offer unparalleled job opportunities that propel your career forward while contributing to a legacy of engineering excellence.

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Learn more about General Motors
Size
157,000 employees
Market Cap
$46.9 billion
Industry
Net Income
$6.4 billion
Founded
1908
5 Year Trend
-3.2%
Revenue
$122.4 billion
NASDAQ

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