Senior Research Scientist - Generative World Models for Autonomous Driving and Physical AI

NVIDIA•Us, CA

About The Position

We are seeking an outstanding Research Scientist or Research Engineer with a passion for synthetic data generation and its application to training autonomous driving models of tomorrow. As part of NVIDIA's Physical AI Platform Research team, you will drive modern research at the intersection of AI, simulation, and autonomy. You will help develop the next generation of secure self-driving vehicles and Physical AI! This role requires outstanding software engineering abilities combined with deep expertise in innovative AI and simulation technologies, including generative world models, end-to-end driving, reasoning, and vision-language models. The ideal candidate will have experience translating research into scalable, production-ready solutions for autonomous driving and simulation. They will also have a strong publication record in leading AI and computer vision forums and journals (e.g., NeurIPS, CVPR, ICCV, ECCV, ICLR, ICML, TPAMI). You will develop innovative ways that leverage generative world models and synthetic data to improve the training, evaluation, and generalization of end-to-end driving systems. You should be passionate about advancing the state of the art through both impactful research and technology transfer. Success in this role requires strong analytical thinking, excellent communication skills, and the ability to collaborate effectively across multidisciplinary teams to deliver innovative research with real-world impact.

Requirements

Ph.D. in Computer Science, Electrical Engineering, Robotics, or a related field (or equivalent experience).
6+ years of relevant professional experience with a strong background in deep learning, artificial intelligence, computer vision, machine learning, simulation, or autonomous systems.
Proven research excellence, evidenced by a strong publication record in leading AI and computer vision symposiums and periodicals (e.g., NeurIPS, CVPR, ICCV, ECCV, ICLR, ICML, TPAMI), along with experience translating research into impactful, real-world systems.
Exceptional software engineering skills, including expert-level programming in Python and experience building scalable machine learning systems and contributing to large, collaborative codebases.
Hands-on experience in one or more of these areas is required: synthetic data generation, generative environment representations, or simulation.
Experience in end-to-end autonomous driving, vision-language models, foundation models, or reasoning for embodied AI is also relevant.
Strong communication and collaboration skills.
Able to work effectively with diverse research and engineering groups and communicate complex technical ideas.
Drives projects from conception to deployment.
Self-motivated, curious, and driven by making a difference, with a passion for advancing the state of the art while delivering research that influences products deployed at scale.

Nice To Haves

First-author publications in leading peer-reviewed AI and computer vision conferences or journals, for example, NeurIPS, CVPR, ICCV, ECCV, ICML, ICLR, or IEEE TPAMI.
Hands-on software engineering experience developing production-quality AI systems for autonomous vehicles, 3D computer vision, generative world and foundation models, video understanding, or large-scale simulation.
Demonstrated experience translating brand-new research into scalable, real-world products, from early-stage prototyping to deployment.
Experience leading or mentoring research projects, collaborating with diverse groups, and driving technical direction in fast-paced research environments.
Contributions to open-source projects, widely adopted research artifacts, or technologies that have produced measurable effects within the broader AI community or industry.

Responsibilities

Research, prototype, and develop new techniques using synthetic data, generative world models, and simulation. The goal is to improve training, evaluation, and generalization of next-generation autonomous driving systems.
Collaborate across research and product organizations to translate new AI advances into scalable technologies.
Develop positive relationships with internal research teams, engineering, and product groups to accelerate innovation.
Drive the future of safe autonomous driving by crafting the research direction and technical roadmap of Alpamayo.
Advance safe, robust, and scalable Level 4 autonomous vehicle capabilities through meaningful research and innovation transfer.