Principal Machine Learning Engineer

General Motors (GM)

Remote Hybrid

Quick summary

Work type: Remote
Location: Sunnyvale, CA
Salary: $296,300–$453,200 / yr
Posted: 79 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $226k

This role $375k

$142k most similar roles pay here $487k

This role pays more than 99% of similar roles. Most pay $194,500–$256,750 — the shaded band above. At the midpoint, this role pays about $375k versus about $226k for comparable roles.

Based on 240 similar postings.

Employer

About General Motors (GM)

General Motors (GM) is a leading American multinational automotive corporation founded in 1908 and headquartered in Detroit, Michigan.

General Motors (GM) currently has 131 open roles on FindRole.

Listed pay typically runs $170,000–$258,500 across 75 roles with salary data.

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View all roles at General Motors (GM)

At a glance

TL;DR · Principal Machine Learning Engineer

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As a Principal AI Engineer at our company, you will lead the design and advancement of our AI platform, focusing on large-scale training and cloud inference to enable next-generation autonomous driving systems. Your daily responsibilities include architecting and optimizing core infrastructure for massive-scale model training, collaborating with data scientists and engineers to streamline workflows from research to production, and establishing best practices for reliability and performance. You will drive efficiency in distributed training and data processing pipelines while providing technical leadership and mentorship to teams. The role requires expertise in Python, PyTorch (preferred), TensorFlow, and proficiency in C++ for critical components. Experience with distributed systems, GPU computing, and cloud environments is essential as you tackle complex challenges in AI scalability and performance optimization.

Skills

Python PyTorch Distributed Training AWS GCP Azure GPU Computing C++ Profiling Analysis Debugging Optimization Distributed Systems Cloud Environments

What you'll do

Architect and optimize core AI/ML platform infrastructure for massive-scale model training.
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 to teams on platform design and architecture.
Partner with cross-functional stakeholders to align platform capabilities with business needs.
Lead the development of next-generation AI-driven driving systems using multi-modal models.

What we're looking for

At least 8 years of professional software engineering experience.
4+ years specializing in AI/ML with expertise in distributed training for large-scale models.
Strong proficiency in Python and PyTorch, preferred over TensorFlow.
Experience with distributed systems, GPU computing, and major cloud environments.
Deep understanding of PyTorch 2.x+, distributed training frameworks, and performance optimization techniques.
Leadership skills to guide teams on platform design and mentor junior engineers.

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