Senior Data Scientist, Security and Networking Research

1 Month ago • 5 Years + • Artificial Intelligence

Job Summary

Job Description

NVIDIA seeks a Senior Data Scientist to join its Security and Networking research team. The role involves developing, implementing, and improving machine learning models for various media types (time series, images, text, audio, video). Responsibilities include optimizing models for performance and scalability, creating efficient pipelines for training and feedback, and collaborating with engineering teams. The ideal candidate possesses a strong background in deep learning, experience with large-scale production systems, and familiarity with inference optimization techniques. Experience with generative models, agents, and RAG is a plus. The position requires excellent programming skills in Python and a deep understanding of machine learning algorithms.
Must have:
  • MS/PhD in relevant field (Deep Learning/ML focus)
  • 5+ years deep learning experience in production
  • Excellent Python programming skills
  • Experience with TensorFlow/PyTorch
  • Large-scale system/pipeline experience
  • Algorithm development and inference optimization
  • Zero/few-shot learning, self-supervised learning
Good to have:
  • Strong software development experience
  • CUDA, CuDNN, TensorRT familiarity
  • Experience with Spark, Hadoop, SQL/NoSQL databases
  • Security and networking background

Job Details

We're looking for a Senior Data Scientist to join a group that specializes in Security and Networking, in relation to ML/AI development. As a Senior Data Scientist you’ll have the opportunity to take an active part in the research and development of NVIDIA’s world-class networking and data center products. This role involves creative problem solving alongside engineering teams, and is key for the continued success of AI networking security.

What you’ll be doing:

  • Developing, implementing and improving models and algorithms across media types, whether time series, images, text, audio or video. 

  • Leveraging data pipelines to efficiently process and transform large volumes of data for training and inference purposes.

  • Optimizing and fine-tuning models for performance, scalability, and resource utilization, considering factors such as latency, efficiency, and cost.

  • Creating efficient pipelines for model training, feedback and improvement.

  • Applying alignment techniques and parameter efficient fine-tuning to improve model performance.

  • Measuring and benchmarking model and application performance to drive improvements.

  • Driving the gathering, building, and annotation of domain specific datasets for benchmarking and training. 

  • Collaborating closely with software and hardware engineers on new features and improvements. Participate in developing and reviewing code, design documents, use case reviews, and test plan reviews.

What we need to see:

  • MS/PhD with expertise in Computer Science, Computer Engineering, Electrical Engineering or related field with a focus on Deep Learning or Machine Learning.

  • 5+ years of experience in deep learning and machine learning in a production environment.

  • Excellent programming skills in Python with software design fundamentals.

  • Hands-on experience with deep learning development frameworks and libraries (e.g. TensorFlow, PyTorch).

  • Experience with large scale production systems and pipelines, with a track record of developing production-grade models

  • Strong algorithm development experience, with knowledge of inference optimization techniques such as model distillation, quantization, pruning.

  • Experience with algorithms including zero/few-shot learning, self-supervised and unsupervised learning and generative AI models for synthetic data creation.

  • Experience with generative models, agents and RAG (including vector databases and reranking algorithms).

  • You are proactive, take full ownership of your deliverables, have a can-do approach, and are excited to learn, explore and apply your skills and creativity to some of the most challenging and rewarding problems in the field.

Ways to stand out from the crowd:

  • Strong software development experience

  • Familiarity with GPU based technologies like CUDA, CuDNN and TensorRT.

  • Experience with tools for data processing and storage (e.g. Apache Spark, Hadoop, SQL databases, NoSQL databases). 

  • Security and networking background, with knowledge of security protocols, network architectures, firewalls, intrusion detection systems, and other relevant security and networking concepts

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.

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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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