Data Scientist

2 Months ago • 5 Years + • Research & Development

Job Summary

Job Description

NVIDIA's Diag Team seeks a Data Scientist to develop a real-time analytics system and ML/DL pipelines for GPU server manufacturing. Responsibilities include designing and developing ML models, leading DL/ML projects related to NVIDIA products, and participating in data cleanup and validation system development. Collaboration with internal and external teams for data analytics projects is also expected. The role requires expertise in parallel computing, DL/ML algorithms (regression, classification, clustering), and excellent communication skills. Experience with Python, R, C/C++, and relevant libraries (scikit-learn, PyTorch) is beneficial.
Must have:
  • BS/MS in relevant field (5+ years experience)
  • Parallel computing expertise
  • DL/ML fluency (statistics, anomaly detection)
  • Regression, classification, clustering knowledge
  • Excellent communication skills
Good to have:
  • R, Python, C/C++ programming
  • Linux skills
  • Experience with sklearn, scipy, numpy, pandas, matplotlib, pytorch, NLP
  • Deep understanding of DL models (Transformers, MLPs, Convolution)
Perks:
  • Competitive salary
  • Generous benefits package

Job Details

NVIDIA Diag Team is now seeking an extraordinary Data Scientist to solve challenges in the GPU server manufacturing process. As a team member, you will be designing a Machine Learning / Deep Learning platform for valuable internal and external products and systems. You will participate in Data Analysis and Reporting system development and communicating with internal and external customers.

What you'll be doing:

  • Develop a high-performance and high-availability in-house real-time analytics system with other engineers from different teams

  • We will also design and develop various ML pipelines and train and evaluate ML models

  • Lead many DL/ML projects related to various NVIDIA products in GPU server areas

  • Participate in the development of an automatic data cleanup and validation system owned by your team

  • At the same time, you will communicate with external teams to help them in their Data Analytics projects

What we need to see:

  • BS or MS degree in one of the areas of Electrical Engineering, Computer Engineering, Computer Science (or equivalent) with 5+ years of meaningful work experience

  • Fully understand parallel computing on multi-threads and multi-processes

  • You are expected to be fluent in DL/ML (Statistics, Fraud/Anomaly detection, A/B testing, etc) and Data Analytics

  • Flawless understanding of Regression, Classification, Clusterization (transactional and real variables), and embedding methodologies, their pros/cons are very significant

  • We expect to see excellent communication skills, ability to document and present the current status and final project deliveries

  • Intermediate/upper-intermediate oral and written technical English

  • Skills of working in an internationally distributed team

  • Self-motivated, engaged, eager for self-education

Ways to stand out from the crowd:

  • We appreciate additional programming skills in R, Python, C/C++ as well as it's important to have basic Linux skills

  • Experience in any of sklearn, scipy, numpy, pandas, matplotlib, pytorch, NLP, and searching/indexing

  • Deep understanding of DL models development (Transformers, MLPs, Convolution) is valuable

With competitive salaries and a generous benefits package, NVIDIA is widely considered to be one of the most desirable employers in the world. We have some of the most brilliant and talented people in the world working for us. If you are creative, autonomous and love a challenge, we want to hear from you. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

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About The Company

Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and is fueling the creation of the metaverse. NVIDIA is now a full-stack computing company with data-center-scale offerings that are reshaping industry.

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