Staff AI/ML Engineer

General Motors•Sunnyvale, CA

55d

About The Position

As a Staff AI/ML Engineer, you will be a technical expert within the AV ML Infra team, driving the design and implementation of scalable ML infrastructure solutions. You will influence the direction of our technical projects, provide mentorship to peers, and help shape the adoption of best practices across GM's ML infrastructure. This is an individual contributor/Tech Lead role focused on deep technical impact rather than team management. 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

8+ years of experience, with a strong background in large-scale distributed systems preferred.
3+ 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 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.

Benefits

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.

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