Staff AI/ML Engineer, AV ML Infra
We’re General Motors (GM), a company driving the future of mobility with advanced self-driving and electric vehicle technologies.
We’re building the world’s most innovative autonomous vehicles to safely connect people to the places, things, and experiences they care about. We believe self-driving vehicles will help save lives, reshape cities, give back time in transit, and restore freedom of movement for many.
GM employees have the opportunity to grow and develop while learning from leaders at the forefront of their fields. With a culture of internal mobility, there’s an opportunity to thrive in a variety of disciplines. This is a place for dreamers and doers to succeed.
If you are looking to play a part in making a positive impact in the world by advancing the revolutionary work of self-driving vehicles, join us.
The AV ML Infra team at GM builds ML infrastructure designed to meet the unique demands of AI and ML innovation, supporting a wide range of use cases across teams such as Embodied AI, Simulation, Data Science, and more. We enable scalable and efficient ML experimentation, enhance the productivity of ML engineers, and drive the adoption of cutting-edge ML techniques.
Our ML infrastructure includes:
Together, these tools and systems empower GM to tackle the complexities of autonomous driving technology and expedite our path to commercialization.
Position Overview:
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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.
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Collaboration: Engage effectively in team planning, code reviews, and design discussions, considering the impact of projects across multiple teams while proactively managing conflicts.
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Mentorship & Recruitment: Conduct technical interviews with calibrated standards, onboard, and mentor engineers and interns, fostering a culture of growth and knowledge sharing.
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Proficiency in building scalable infrastructure on the cloud using Python, C++, Golang, or similar languages.
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A Bachelor’s, Master’s, or Ph.D. in Computer Science, Electrical Engineering, Mathematics, Physics, or a related field; or equivalent practical experience.
