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Senior ML Compiler Engineer

AT General Motors
General Motors

Senior ML Compiler Engineer

Mountain View, CA

Description

Remote : This role is based remotely but if you live within a 50-mile radius of [Atlanta, Austin, Detroit, Warren, Milford or Mountain View], you are expected to report to that location three times a week, at minimum.

Role: We are looking for a deep learning compiler engineer to build out our ML compiler for deploying machine learning models to a variety of ML hardware accelerators. You will develop and enhance GM's internal ML compiler for high performance, usability, and retargetability by leveraging open-source technology like MLIR and LLVM.

The Autonomous Vehicle (AV) software stack heavily relies on machine learning to perform various critical tasks. In this role, you will collaborate closely with engineers and researchers from different AV Engineering teams (e.g., Computer Vision, Perception, platform) to scope out system requirements while engaging with AV hardware teams to understand the target hardware platform and its constraints.

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What You'll Do

  • Build out a retargetable compiler pipeline for on-car ML accelerators


  • Build tooling to improve the usability of the compiler, enabling ML engineers to understand deployability, performance and accuracy of compiled ML models


  • Support deployment of innovative ML models on the car


  • Influence compiler architecture decisions and strategy within GM

Additional Description

Your Skills & Abilities:

  • 3+ years of experience in the field of compilers


  • Experience with ML frameworks (e.g., PyTorch, TensorFlow, JAX) and software stack (e.g., 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

  • Experience developing and deploying machine learning models


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


  • Experience with ML accelerators and hardware architecture

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 $158,000-$241,900. 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.

Relocation: This job may be eligible for relocation benefits.

About GM

Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.

Why Join Us

We believe we all must make a choice every day - individually and collectively - to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.

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Non-Discrimination and Equal Employment Opportunities (U.S.)

General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.

All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws.

We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire.

Accommodations

General Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, email us [email protected] or call us at 800-865-7580. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.

Client-provided location(s): Mountain View, CA, USA
Job ID: General_Motors-JR-202510490
Employment Type: Full Time

Perks and Benefits

  • Health and Wellness

    • Health Insurance
    • Health Reimbursement Account
    • Dental Insurance
    • Vision Insurance
    • Life Insurance
    • Short-Term Disability
    • Long-Term Disability
    • FSA
    • HSA
    • HSA With Employer Contribution
  • Parental Benefits

    • Birth Parent or Maternity Leave
    • Non-Birth Parent or Paternity Leave
    • Adoption Leave
    • Fertility Benefits
    • Adoption Assistance Program
    • Family Support Resources
  • Work Flexibility

    • Flexible Work Hours
    • Remote Work Opportunities
    • Hybrid Work Opportunities
  • Office Life and Perks

    • Casual Dress
    • Happy Hours
    • On-Site Cafeteria
  • Vacation and Time Off

    • Paid Vacation
    • Paid Holidays
    • Personal/Sick Days
    • Leave of Absence
  • Financial and Retirement

    • 401(K)
    • 401(K) With Company Matching
    • Performance Bonus
    • Relocation Assistance
    • Stock Purchase Program
  • Professional Development

    • Tuition Reimbursement
    • Learning and Development Stipend
    • Promote From Within
    • Mentor Program
    • Shadowing Opportunities
    • Access to Online Courses
    • Lunch and Learns
    • Internship Program
  • Diversity and Inclusion

    • Diversity, Equity, and Inclusion Program
    • Woman founded/led
    • Employee Resource Groups (ERG)

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