Job Summary

NVIDIA is seeking a highly motivated Data Science Research Scientist to join its AI Research organization. In this role, you will conduct cutting-edge research in machine learning, deep learning, generative AI, and large-scale data analytics to develop innovative algorithms that power next-generation AI products and platforms.

You will collaborate with world-class researchers, software engineers, and product teams to transform advanced research into scalable solutions for industries including autonomous vehicles, healthcare, robotics, cloud computing, cybersecurity, and accelerated computing.

Key Responsibilities

• Conduct research in machine learning, deep learning, statistical modeling, and artificial intelligence.
• Design, develop, and evaluate novel algorithms for predictive analytics and AI applications.
• Build and optimize large-scale machine learning models using structured and unstructured datasets.
• Research and improve Large Language Models (LLMs), Generative AI, and multimodal AI systems.
• Design experiments, analyze results, and present technical findings to research and engineering teams.
• Develop scalable data processing pipelines for model training and evaluation.
• Collaborate with software engineers to transition research prototypes into production-ready AI solutions.
• Publish research findings in leading AI and data science conferences and journals when appropriate.
• Stay current with emerging technologies and advancements in AI, machine learning, and data science.
• Mentor junior researchers and contribute to the organization’s innovation initiatives.
• Optimize model performance, scalability, explainability, and efficiency.
• Ensure responsible AI practices, including fairness, transparency, privacy, and model governance.

Required Qualifications

• Master’s or Ph.D. in Data Science, Computer Science, Artificial Intelligence, Machine Learning, Statistics, Applied Mathematics, or a related quantitative field.
• 3–7+ years of experience in machine learning research, AI, or data science.
• Strong understanding of supervised, unsupervised, reinforcement learning, and deep learning techniques.
• Experience with Large Language Models (LLMs), transformer architectures, or generative AI is highly desirable.
• Proficiency in Python and common data science libraries.
• Experience working with large datasets and distributed computing environments.
• Strong analytical, problem-solving, and research skills.
• Excellent written and verbal communication skills.

Preferred Qualifications

• Publications in top AI conferences such as NeurIPS, ICML, ICLR, CVPR, ACL, EMNLP, or KDD.
• Experience with distributed machine learning frameworks and GPU computing.
• Familiarity with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform.
• Experience with Retrieval-Augmented Generation (RAG), vector databases, or AI agents.
• Knowledge of MLOps, model deployment, and scalable AI infrastructure.

Technical Skills

Programming Languages

• Python
• SQL
• C++
• Java
• R

AI & Machine Learning

• Machine Learning
• Deep Learning
• Generative AI
• Large Language Models (LLMs)
• Reinforcement Learning
• Transfer Learning
• Natural Language Processing (NLP)
• Computer Vision
• Time Series Forecasting

Frameworks & Libraries

• PyTorch
• TensorFlow
• JAX
• Scikit-learn
• XGBoost
• Hugging Face Transformers

Data Engineering & Big Data

• Apache Spark
• Apache Kafka
• Hadoop
• Delta Lake
• Databricks

Cloud & MLOps

• AWS
• Microsoft Azure
• Google Cloud Platform
• Docker
• Kubernetes
• MLflow
• Kubeflow

Databases

• PostgreSQL
• Snowflake
• BigQuery
• MongoDB
• Vector Databases (Pinecone, Weaviate, FAISS)

Visualization

• Tableau
• Power BI
• Matplotlib
• Plotly

Soft Skills

• Research and Innovation
• Critical Thinking
• Statistical Analysis
• Problem Solving
• Collaboration
• Technical Communication
• Leadership
• Project Management
• Adaptability
• Continuous Learning

Benefits

• Competitive Salary
• Annual Performance Bonus
• Restricted Stock Units (RSUs)
• Medical, Dental, and Vision Insurance
• Paid Time Off (PTO) and Paid Holidays
• Employee Stock Purchase Plan (ESPP)
• Professional Development and Conference Sponsorship
• Tuition Reimbursement
• Flexible Hybrid Work Environment
• Wellness Programs
• Employee Assistance Program (EAP)