Senior ML Engineer, ML compute

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

Compensation

• 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.

Relocation

This job may be eligible for relocation benefits.

Remote/Hybrid

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.

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