LLM & Machine Learning Researcher Student
Core
Develop and advance an in-house agentic AI system to optimize NVIDIA's product production processes.
Role type
Master's/PhD student LLM & Machine Learning Researcher
Builds
Agentic AI systems for internal product production optimization
Domain
Semiconductor manufacturing / AI / Machine Learning
Deliverable
production ML models
Required skills
agentic AI tools usage, supervised learning, feature engineering, model evaluation, Python, scikit-learn, XGBoost, CatBoost, Pandas, statistical modeling, data structures, numerical computing, version control
Preferred skills
experimental design, rigorous model evaluation, RAG, fine-tuning, agentic pipelines, creative novel approaches
Technologies
Python, scikit-learn, XGBoost, CatBoost, Pandas, Git
Responsibilities
Analyze outputs and behavior of LLM-based agentic systems to identify failure patterns; Research, design, and train classical ML models for prediction, classification, and optimization; Investigate and evaluate ML components and feature selection methods; Explore and apply LLM capabilities including prompt engineering, RAG, fine-tuning, and agentic tool use; Analyze model failures and data gaps to prototype improvements; Work with software engineers to translate research insights into engineering improvements
Seniority
Student (Master's or PhD candidate)
