LLM & Machine Learning Researcher Student

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation fueled by great technology and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing, where our GPUs power computers, robots, and self‑driving cars that can understand the world. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact.

We are looking for a master's student or PhD candidate in Computer Science, Electrical/Computer Engineering, Statistics, or a related field to join our product‑engineering data‑science team as an LLM & Machine Learning Student Researcher. You will help develop and advance an in‑house agentic AI system that optimizes NVIDIA's product production processes. Under the mentorship of senior applied scientists, you will contribute to research, development, and prototyping of ML components and LLM-powered solutions evaluated in real production environments.

What you'll be doing:

Analyze outputs and behavior of LLM-based agentic systems, identify failure patterns, and propose data-driven improvements.
Research, design, and train classical ML models (e.g., gradient boosting, ensemble methods) for prediction, classification, and optimization tasks within the production pipeline.
Investigate and evaluate ML components, algorithms, and feature selection methods to improve system performance and robustness.
Explore and apply LLM capabilities — including prompt engineering, RAG, fine-tuning, evaluation, and agentic tool use — to production-relevant problems.
Analyze model failures and data gaps, then propose and prototype improvements to features, algorithms, and system design.
Work closely with software engineers and applied scientists to translate research insights into actionable engineering improvements.

What we need to see:

Currently enrolled in a Master's or PhD program in Computer Science, Information Systems, Engineering, Statistics, or a closely related field.
Proficiency with agentic AI tools (e.g., ChatGPT, Claude) for research, prototyping, and productivity.
Solid foundations in machine learning, including supervised learning, feature engineering, and model evaluation.
Programming skills in Python, with experience in at least some of: scikit-learn, XGBoost, CatBoost, and Pandas.
Understanding of ML/DL algorithms and statistical modeling, and comfort working with data structures and numerical computing.
Experience with modern software‑development practices and version‑control systems (e.g., Git).

Ways to stand out from the crowd:

Ability to cut through complexity — knowing what matters, drilling into the right details, and keeping the business goal in sight.
Strong statistical foundations with hands-on experience in experimental design and rigorous model evaluation.
Familiarity with LLM concepts such as RAG, fine-tuning, or agentic pipelines.
A track record of creative, novel approaches over off-the-shelf defaults.

NVIDIA is widely regarded as one of the technology industry’s most desirable employers and offers competitive compensation and comprehensive benefits for eligible student roles. We are an equal opportunity employer and highly value diversity; we do not discriminate on the basis of any legally protected characteristic and provide reasonable accommodation for individuals with disabilities throughout the application and employment process.