Descripción
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.
Are you passionate about pushing the boundaries of multimodal artificial intelligence and seeing your models run on physical, real-world systems? As a Senior Research Scientist specializing in Vision-Language Models (VLMs) and Vision-Language-Action models (VLAs), you will be a key contributor in the AI Research organization. You will focus on advancing the frontier of machine learning to solve complex, open-ended problems in autonomous driving.
In this role, you will design, train, and prototype state-of-the-art foundational models that enable our vehicles to understand complex driving environments, reason through difficult edge cases, and map visual-textual inputs directly to safe driving actions. Your primary challenge will be balancing high-capacity AI reasoning with the stringent latency and compute constraints of onboard vehicle hardware. You will actively contribute to our technical direction, collaborate with deployment teams, and publish your findings at top-tier global AI conferences.
What You’ll Do
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Research, design, and implement advanced Vision-Language Models and Vision-Language-Action models to enhance the autonomous vehicle’s semantic understanding and decision-making capabilities.
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Develop and execute techniques for onboard model optimization, including quantization, distillation, and architecture search, to ensure large foundational models run efficiently on vehicle edge hardware.
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Partner closely with downstream engineering teams (perception, planning, and control) to integrate foundational VLM/VLA outputs into the active vehicle software stack.
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Contribute to the technical roadmap by identifying high-impact research areas and translating strategic machine learning priorities into concrete, actionable prototypes.
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Provide technical mentorship to junior researchers and engineers, fostering a culture of excellence and collaborative innovation.
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Secure intellectual property through patents and represent the company externally by publishing peer-reviewed research at top-tier machine learning conferences.
Your Skills & Abilities (Required Qualifications)
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Ph.D. in Machine Learning, Robotics, Computer Science, Electrical Engineering, or a related technical field.
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2+ years of experience in AI/ML research and applied development.
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Expertise in modern ML architectures (transformers, generative AI, multimodal systems).
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Strong programming skills in Python.
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Strong communication, collaboration, and mentoring abilities
What Will Give You A Competitive Edge (Preferred Qualifications)
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Demonstrated research impact in AI/ML technologies either through important publications in top conferences or demonstrated contribution to industry leading systems.
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AV/ADAS experience
Remote: This role is based remotely but if you live within a 50-mile radius of a GM office, you are expected to report to that location three times per 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 the California Bay Area.
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The salary range for this role is $170,600.00 to $261,300.00. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position.
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Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.
Benefits:
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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.
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Información sobre diversidad
General Motors se compromete a ser un lugar de trabajo en el cual no solo no haya discriminación indebida, sino que fomente con sinceridad la inclusión y el sentido de pertenencia. Creemos firmemente que la diversidad del personal crea un entorno en el cual nuestros empleados pueden prosperar y desarrollar mejores productos para nuestros clientes. Instamos a los candidatos interesados a que revisen las responsabilidades y aptitudes clave para cada puesto y se postulen para los puestos que coincidan con sus habilidades y capacidades. Es posible que, cuando corresponda, se les pida a los solicitantes que están en el proceso de contratación que completen satisfactoriamente una o más evaluaciones relacionadas con su función y/o una evaluación previa al empleo antes de comenzar a trabajar. Para obtener más información, visite Cómo contratamos.
Declaración de igualdad de oportunidades en el empleo (EE.UU.)
General Motors se enorgullece de ser un empleador que ofrece igualdad de oportunidades. Todos los solicitantes calificados serán tenidos en cuenta para el empleo sin distinción de raza, color, religión, sexo, orientación sexual, identidad de género, nacionalidad, discapacidad o condición de veterano protegido.
Adecuaciones (EE.UU. y Canadá)
General Motors ofrece oportunidades a todos los solicitantes de empleo, incluyendo las personas con discapacidades. Si necesita una adecuación razonable para ayudarle con su búsqueda o solicitud de empleo, envíenos un correo electrónico a [email protected] o llámenos al 800-865-7580. En su correo electrónico, incluya una descripción del puesto específico que está solicitando, así como el título del empleo y el número de solicitud del puesto que está solicitando.




