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Sunnyvale, California, United States
Hybrid
Not Available
Job Description
At General Motors, our product teams are redefining mobility. Through a human-centered design process, we create vehicles and experiences that are designed not just to be seen, but to be felt. We’re turning today’s impossible into tomorrow’s standard —from breakthrough hardware and battery systems to intuitive design, intelligent software, and next-generation safety and entertainment features.
Every day, our products move millions of people as we aim to make driving safer, smarter, and more connected, shaping the future of transportation on a global scale.
Role: As a Staff Research Scientist in the AI Research organization, you will be advancing the frontier of machine learning to solve challenging problems in autonomous driving. You will design state-of-the-art algorithms that open new possibilities for our vehicles. Additionally, you will help shape technical directions, mentor, and publish at top conferences.
About the Organization: The AI Research team advances the state-of-the-art in AI for autonomous vehicles. We research, design, and prototype advanced AI/ML techniques (e.g., foundation models, VLAs, diffusion, image/video generation, self-supervised learning, IL, RL) that help our vehicles unlock new autonomous capabilities. Join a collaborative and innovative team redefining autonomy.
What You’ll Do
Research, design, and prototype advanced ML approaches (e.g., foundation models, VLAs, diffusion, image/video generation, self-supervised learning, IL, RL) to advance the state-of-the-art in autonomous driving.
Influence technical roadmaps, shaping strategic ML priorities aligned with company objectives and product milestones.
Provide technical mentorship and vision.
Collaborate closely with multidisciplinary engineering groups, helping foster ML innovation across teams.
Represent GM externally through publications, patents, and participation in top conferences.
Your Skills & Abilities (Required Qualifications)
Ph.D. in Machine Learning, Robotics, Computer Science, Electrical Engineering, or a related technical field.
5+ years of experience in AI/ML research and applied development.
Deep expertise in modern ML architectures (transformers, generative AI, multimodal systems).
Strong programming skills in Python.
Excellent communication, collaboration, and mentoring abilities, comfortable influencing technical strategy and guiding ML excellence across the organization.
What Will Give You A Competitive Edge (Preferred Qualifications)
Demonstrated research impact in AI/ML technologies either through important publications in top conferences or demonstrated contribution to industry leading systems.
AV/ADAS experience
Remote: This role is based remotely but if you live within a 50-mile radius of Mountain View, you are expected to report to that location three times a week, at minimum.
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 $218,800.00 to $335,300.00. 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:
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.
This job may be eligible for relocation benefits.
Company Vehicle: Upon successful completion of a motor vehicle report review, you will be eligible to participate in a company vehicle evaluation program, through which you will be assigned a General Motors vehicle to drive and evaluate. Note: program participants are required to purchase/lease a qualifying GM vehicle every four years unless one of a limited number of exceptions applies.
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About GM
Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.
Why Join Us
We believe we all must make a choice every day – individually and collectively – to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.
Benefits Overview
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.
Non-Discrimination and Equal Employment Opportunities (U.S.)
General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.
All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws.
We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire.
Accommodations
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