Principal AI/ML Engineer, AV ML Infra

GM•Sunnyvale, CA

2d•Hybrid

About The Position

The Principal AI/ML Engineer will lead a growing organization, guiding the AV ML Infra team in achieving its mission while shaping long-term vision and execution strategies across GM’s AI and ML efforts. This leadership role will drive a transformative leap in our infrastructure capabilities to meet the scale we anticipate. The leader will articulate a clear vision and strategy, design an organizational structure to enable effective execution, and cultivate strong partnerships across cross-functional teams and stakeholders. Note: This role is part of an ML infrastructure engineering team and does not involve applying machine learning models for specific tasks. The focus is on developing infrastructure products that empower GM teams to perform machine learning and data science at scale.

Requirements

10+ years of experience, with a strong background in large-scale distributed systems preferred.
5+ years of experience leading and driving large-scale initiatives.
Proficiency in building scalable infrastructure on the cloud using Python, C++, Golang, or similar languages.
Experience working with relational and NoSQL databases.
Demonstrated ability to develop and maintain systems at scale.
A Bachelor’s, Master’s, or Ph.D. in Computer Science, Electrical Engineering, Mathematics, Physics, or a related field; or equivalent practical experience.
A passion for autonomous vehicle technology and its transformative potential.
Strong attention to detail and a commitment to accuracy.
A proven track record of efficiently solving complex problems.
A startup mentality with a willingness to embrace uncertainty and wear multiple hats.

Nice To Haves

Experience with Google Cloud Platform, Microsoft Azure, or Amazon Web Services.
Experience with open-source orchestration platforms such as Kubeflow, Flyte, Airflow, etc.
Experience with model serving frameworks such as RayServe, vLLM, Triton.
Experience with Kubernetes.
Understanding of Machine Learning (ML) models/pipelines.
Python/C++/Golang proficiency.
Relevant publications.

Responsibilities

Design & Implementation: Utilize the latest cloud technologies (GCP/Azure) to design, implement, and test scalable distributed computing and data processing solutions in the cloud.
Project Ownership: Take ownership of technical projects from inception to completion, contribute to the product roadmap, and make informed decisions on major technical trade-offs.
Collaboration: Engage effectively in team planning, code reviews, and design discussions, considering the impact of projects across multiple teams while proactively managing conflicts.
Mentorship & Recruitment: Conduct technical interviews with calibrated standards, onboard, and mentor engineers and interns, fostering a culture of growth and knowledge sharing.