Job Details

The Role:

We are seeking a Principal AI Engineer to lead the design and advancement of our AI platform. You will play a key role in shaping the infrastructure that powers large-scale training and cloud inference. This includes accelerating training throughput, scaling multi-modal models, and enabling the next generation of AI-driven driving systems. We're tackling challenges across distributed training, training efficiency, DDP/FSDP, data processing pipelines, and Pytorch model optimization. This is a highly impactful position where your technical leadership will define how we scale AI to achieve autonomy.

What You'll Do:

• Architect, build, and optimize core AI/ML platform infrastructure to support massive-scale model training.
• Collaborate with data scientists, ML engineers, and software developers to enable seamless workflows from research to production.
• Drive efficiency in large-scale distributed training and data processing pipelines.
• Establish best practices for reliability, scalability, and performance across the AI/ML platform.
• Provide technical leadership and mentorship, guiding teams on platform design, architecture decisions, and emerging technologies.
• Partner with cross-functional stakeholders to align platform capabilities with business needs and strategic AI initiatives.

Your Skills & Abilities (Required Qualifications):

• Bachelor's degree or higher in Computer Science, related field, or equivalent experience.
• 8+ years of professional software engineering experience.
• 4+ years of specialized experience in AI/ML domain (e.g., enabling distributed training for large-scale models).
• Strong programming skills in Python, with proficiency in frameworks such as PyTorch (preferred) or TensorFlow.
• Experience with distributed systems, GPU computing, and cloud environments (AWS, GCP, or Azure).
• Comfortable operating in highly ambiguous and dynamic environments.
• Willingness to travel to Sunnyvale, CA as needed.

What Will Give You a Competitive Edge (Preferred Qualifications):

• Proven track record of self-motivation, execution, and delivering impact.
• Deep expertise with PyTorch 2.x+ and distributed training frameworks.
• Strong skills in profiling, analysis, debugging, and optimizing training performance (e.g., avoiding memory fragmentation, operation fusion).
• Proficiency in C++ for performance-critical components.
• Experience leading cross-functional projects and aligning diverse stakeholders on priorities.

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 $197,600 to $374,200. 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.

Work Location: 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.