Senior Software Engineer - AI Compute Platform

Job Description

About the Team:

The ML Compute Platform is part of the AI Compute Platform organization within Infrastructure Platforms. Our team owns the cloud-agnostic, reliable, and cost-efficient compute backend that powers GM AI. We’re proud to serve as the AI infrastructure platform for teams developing autonomous vehicles (L3/L4/L5), as well as other groups building AI-driven products for GM and its customers.

We enable rapid innovation and feature development by optimizing for high-priority, ML-centric use cases. Our platform supports the training and deployment of state-of-the-art (SOTA) machine learning models with a focus on performance, availability, concurrency, and scalability. We’re committed to maximizing GPU utilization across platforms (B200, H100, A100, and more) while maintaining reliability and cost efficiency.

About the Role:

We are looking for a Senior Software Engineer to join our team and help us scale our platform for performance, reliability, and usability. You’ll be responsible for building critical backend services, integrating with GPU hardware and orchestration systems, and driving improvements to both system architecture and user experience.

This is a hands-on engineering role that requires a strong background in distributed systems, infrastructure, and a product mindset with a keen eye for user experience.

Your Skills & Abilities (Required Qualifications)

• Design core platform backend software components
• Experience cloud platforms like GCP, Azure
• Thrive in a dynamic, multi-tasking environment with ever-evolving priorities. Interface with other teams to incorporate their innovations and vice versa
• Analyze and improve efficiency, scalability, and stability of various system resources
• Proactively identify, drive and design large initiatives across GM ML ecosystem
  
  
  

At a Minimum We'd Like You To Have

• 5+ years of industry experience\
• Expertise in either Go, C++, Python or other relevant coding languages
• Strong background with kubernetes at scale
• Relevant experience building large-scale with distributed systems
• Experience leading and driving large scale initiatives
• Experience working with Google Cloud Platform, Microsoft Azure, or Amazon Web Services
  
  
  

What Will Give You a Competitive Edge (Preferred Qualifications)

• Hands-on experience in ML platforms
• Experience with GPU/TPU optimizations
• Experience with training frameworks like PyTorch, TorchX
• Experience with Ray framework

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• Leadership/active participation in the open source community
• Experience infrastructure applications or similar experience
  
  
  

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 $155,420 to $395,900. 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.
• 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.
  
  
  

Benefits:

• 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.
  
  
  

Relocation: This job may be eligible for relocation benefits.

Remote/Hybrid: This role is based remotely but if you live within a 50-mile radius of Mountain View, you are expected to report to that location three times a week, at minimum.

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.

Benefits Overview

From day one, we're looking out for your well-being–at work and at home–so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources.

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

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