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.
What you'll be doing:
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.
What we need to see:
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.
Ways to stand out from the crowd:
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.
You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.Skills Required
- Ph.D. in Computer Science, Electrical Engineering, Robotics, or a related field (or equivalent experience).
- 6+ years of relevant professional experience in deep learning, AI, computer vision, simulation, or autonomous systems.
- Proven research excellence with a strong publication record in top AI and computer vision venues (NeurIPS, CVPR, ICCV, ECCV, ICLR, ICML, TPAMI).
- Expert-level programming in Python.
- Experience building scalable machine learning systems and contributing to large, collaborative codebases.
- Hands-on experience in synthetic data generation, generative environment representations, or simulation.
- Experience or familiarity with end-to-end autonomous driving, vision-language models, foundation models, or reasoning for embodied AI.
- Strong communication and collaboration skills; ability to drive projects from conception to deployment.
- First-author publications in leading peer-reviewed AI and computer vision conferences or journals.
- Hands-on software engineering experience developing production-quality AI systems for autonomous vehicles, 3D computer vision, or large-scale simulation.
- Demonstrated experience translating research into scalable, real-world products and mentoring or leading research projects.
- Contributions to open-source projects or widely adopted research artifacts.
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
