Research Scientist, ML Systems - New College Grad 2026

NVIDIA•Westford, CA

About The Position

Today, NVIDIA is tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, encouraging environment where everyone is inspired to do their best work. Come join the team and see how we can make a lasting impact on the world. We are now looking for a Research Scientist New Graduate with a focus on Machine Learning Systems (MLSys). NVIDIA Research is seeking exceptional systems researchers to contribute to the development of hardware, software, and infrastructure technology for ML systems of all scales. Advances in AI/ML heavily rely on the development of efficient, scalable, resilient, and trustworthy systems for training, fine-tuning, and serving ML models. AI/ML applications are also pushing the limits of both personal devices and warehouse-scale data centers. All layers of AI systems need to be co-designed and co-optimized to maximize performance and energy efficiency, improve scalability, and support emerging algorithms in this space. We are seeking candidates that have a proven track record of research excellence, a broad perspective on systems design across the full hardware/software/infrastructure stack, and depth in one of the layers such as AI/ML systems, operating systems, distributed systems, data management, cloud computing, and computer architecture.

Requirements

Recent graduate with a Ph.D. in CS/CE/EE with a strong background in operating systems, distributed systems, inference and training systems, data management systems, networking, cloud computing, and/or computer architecture (or equivalent experience).
Background with experimental research and development.
Experience with C, C++, Python, and/or scripting languages.
Experience with using AI tools for analysis, design, and code development.

Nice To Haves

A strong publication, patent, and research collaboration history is a huge advantage.
Demonstrated expertise in one specific area with the ability to become the go-to resource within a team having varied backgrounds.

Responsibilities

Understand and analyze the efficiency, scaling, and resilience challenges in ML systems, algorithms, and applications.
Develop creative systems solutions (hardware, software, infrastructure) for future ML systems of all scales.
Contribute to the co-design of next-generation AI/ML algorithms and systems.
Collaborate with a diverse set of research and product teams across the company, spanning software, hardware, AI, and networking.
Publish original research and speak at conferences and events.