Data Scientist

NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 fueled 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. NVIDIA is a “learning machine” that constantly evolves by adapting to new challenges that are hard to address, that only we can pursue, and that matter to the world. This is our life’s work, to amplify human creativity and intelligence. Make the choice to join us today! NVIDIA is seeking a highly skilled and experienced Data Scientist/ Machine Learning Engineer to join our growing team. You will work at the intersection of AI and software engineering, responsible for the design, development, and maintenance of the LLM MLOps platform at NVIDIA.

What You’ll Be Doing:

• Collaborate with team members to identify key metrics and opportunities for improving business processes, products, and services.

• Build, deploy, and maintain data management systems and back-end data infrastructure for our business intelligence pipeline.

• Perform data mining, exploration, analysis, preprocessing, and feature engineering to build high-quality datasets for model training and evaluation.

• Create data visualizations, reports, dashboards, and data audits.

• Develop and maintain robust software solutions to automate data pipelines, model training, validation, deployment, and monitoring in production environments.

• Collaborate with multi-functional teams, including software engineers, data engineers, and product managers, to deploy ML models at scale, ensuring robustness, scalability, and performance.

• Stay current with the latest research and advancements in data science and machine learning and apply innovative techniques to NVIDIA’s products and services.

What We Need To See:

• Master’s degree or PhD in Computer Science, Data Science, Machine Learning, or a related field (or equivalent experience).

• 5+ years of experience in data science, machine learning, or a similar role with a strong focus on developing and deploying ML models.

• Proficiency in programming languages such as Python, R; experience with ML frameworks like TensorFlow, PyTorch, or Scikit-Learn; and experience with data science toolkits such as R, NumPy, and MatLab.

• Deep understanding of machine learning algorithms, statistical analysis, and data mining techniques.

• Experience in working with large datasets, including experience in data preprocessing, feature engineering, and building high-quality training datasets.

• Experience with cloud-based infrastructure.

• Strong problem-solving skills, with the ability to translate sophisticated business challenges into data-driven solutions.

Ways To Stand Out From The Crowd:

• Experience in human annotation tools for GenAI annotation tasks.

• In-depth knowledge of statistical evaluation methodologies/algorithms, metrics for assessing annotated data quality such as Krippendorf's alpha, inter-annotator agreement score.

• Experience deploying models in production environments, including familiarity with cloud-based ML platforms (e.g., AWS SageMaker, Azure ML, Google AI Platform).

• Proven track record of published research or contributions to open-source ML libraries and tools.

• Passion for AI and a demonstrated commitment to advancing the field through innovative research and development.

With competitive salaries and a generous benefits package (www.nvidiabenefits.com ), we are widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to outstanding growth, our best-in-class engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you!