We are looking for an experienced data scientist to join the manufacturing data science team and help us shape our AI solutions, production test predictions, yield forecasting, unsupervised learning, characterization predictions, and anomaly detection across the design and manufacturing process.

As a Senior Data Scientist, you will research, develop, implement, and maintain machine learning & deep learning models and algorithms. You will work closely with different business teams, including data scientists, data engineers, software engineers, and product managers, to drive innovation and ground-breaking solutions. If you genuinely passionate about data science, has a strong background in data research, programming, and possesses excellent problem-solving we'd love to hear from you!

What you’ll be doing:

• Develop and implement machine learning & deep learning models: Design research, develop, and deploy scalable models and algorithms that address complex business challenges in the manufacturing process. Apply various techniques such as supervised and unsupervised learning.

• Data pre-processing and analysis: Collaborate with data scientists and data engineers to collect, clean, pre-process, and transform large and wide datasets. Conduct exploratory data analysis (EDA) to uncover insights and identify patterns that boost the model performance.

• Model evaluation and optimization: Conduct detailed model evaluation metrics and validation to ensure accuracy, reliability, and scalability. Optimize model performance by fine-tuning hyper parameters, feature engineering, and applying techniques such as ensemble learning and continuous learning.

• Deployment and integration: Work closely with software engineers to integrate machine learning models into production systems. Ensure flawless deployment and efficient model inference in real-time environments. Collaborate with DevOps to implement effective monitoring and maintenance strategies.

• Collaborate with multidisciplinary teams: Collaborate with product engineers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions.

What we need to see:

• Master’s degree in Computer Science, Information Systems, Engineering, Statistics, or a related field.

• 5+ years of experience as a data scientist or a similar role, with a consistent record of successfully delivering ML / DL solutions.

• Demonstrated expertise in conducting clustering research.

• Experience with training models over tabular data.

• Strong programming skills in languages such as Python, R, or Java. Experience with frameworks like TensorFlow, PyTorch, or scikit-learn.

• Proficiency in data manipulation, analysis, and visualization using tools like NumPy, pandas, and matplotlib.

• Deep understanding of machine learning algorithms, statistical models, and data structures.

• Familiarity with software development practices and version control systems (e.g., Git).

• Experience with experimental design, A/B testing, and evaluation metrics for ML models.

Ways to stand out from the crowd:

• Strong analytical thinking and problem-solving abilities, with a focus on applying ML techniques to real-world challenges.

• Ability to analyze complicated and wide data sets, identify patterns, and derive significant insights.

• Experience with Large Language Models (LLM) and Natural Language Processing (NLP).

• Proficient in training Reinforcement Learning models.

• Skilled in developing and conducting research in computer vision.

• Self-motivated with a goal to stay updated on the latest methodologies and machine learning technologies.

Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.