À propos de ce poste Staff Research Scientist - VLM / VLA chez General Motors
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.
The Role
Are you ready to redefine mobility and shape the future of autonomous transportation? As a Staff Research Scientist specializing in Vision-Language Models (VLMs), Vision-Language-Action models (VLAs), and Onboard Foundational Models, you will advance the frontier of artificial intelligence to solve the most challenging problems in autonomous driving.
In this role, you will bridge the gap between large-scale multimodal foundational AI and real-time physical systems. You will lead the design, training, and optimization of state-of-the-art models that allow vehicles to deeply understand complex visual scenes, reason through open-ended scenarios, and translate multimodal inputs directly into safe, actionable driving decisions. Crucially, your work will focus not just on cloud-scale intelligence, but on pioneering the techniques required to compress, quantize, and deploy these massive architectures directly onto resource-constrained onboard vehicle hardware. You will help shape strategic technical directions, mentor a world-class team of engineers, and represent our organization at top global artificial intelligence conferences.
What You’ll Do
Research, design, and prototype advanced Vision-Language Models and Vision-Language-Action foundational models tailored for real-time semantic understanding and behavioral prediction in autonomous driving.
Drive the technical strategy for onboard model optimization, leading initiatives in model quantization, pruning, knowledge distillation, and compilation to ensure high-parameter models execute with ultra-low latency on vehicle edge hardware.
Advance multimodal alignment techniques, ensuring seamless integration of camera, radar, LiDAR, and textual/logical prompts into unified foundational architectures.
Influence technical roadmaps and shape strategic machine learning priorities that align with safety requirements, core product milestones, and next-generation vehicle launches.
Provide technical mentorship and long-term vision to a multidisciplinary group of machine learning engineers, software developers, and hardware specialists.
Foster internal innovation by collaborating closely with perception, planning, and infrastructure teams to integrate foundational models into the core autonomous software stack.
Represent the company externally to the global scientific community by publishing original research, securing patents, and presenting at top-tier artificial intelligence and robotics 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
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Benefits Overview
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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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