Senior Data Scientist - Security

Posted Yesterday
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4 Locations
In-Office
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Develop agentic AI and machine learning systems for cybersecurity products, including generative AI, RAG, threat analysis automation, model optimization, data pipelines, dataset development, and multimodal algorithms. Fine-tune and evaluate production-grade models, improve inference performance, and collaborate with software and hardware engineers on product features, code, designs, and testing.
Summary Generated by Built In

We're looking for a Senior Data Scientist to join the AI cybersecurity team in the   Security and Networking Architecture group. 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 security 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 agentic AI systems for security, combining generative models, RAG, and tool-augmented reasoning to automate threat analysis and response workflows.
  • Optimizing and fine-tuning models for performance, scalability, and resource utilization, considering factors such as latency, efficiency, and cost.
  • 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.
  • 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 Python programming skills, strong software design fundamentals, and experience leveraging coding agents in development workflows.
  • 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
  • Experience with agentic AI systems, agent frameworks, and evaluation of agent performance and reliability.
  • Strong algorithm development experience, with knowledge of inference optimization techniques such as model distillation, quantization, pruning.
  • Background with algorithms including zero/few-shot learning, self-supervised and unsupervised learning and generative AI models for synthetic data creation.
  • Experience with fine-tune / training LLM models
  • 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.

What will make you 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 
  • 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.

Skills Required

  • Master's or PhD in Computer Science, Computer Engineering, Electrical Engineering, or a related field focused on deep learning or machine learning
  • 5+ years of deep learning and machine learning experience in a production environment
  • Excellent Python programming skills
  • Strong software design fundamentals
  • Experience leveraging coding agents in development workflows
  • Hands-on experience with deep learning frameworks and libraries such as TensorFlow or PyTorch
  • Experience with large-scale production systems and pipelines
  • Track record of developing production-grade models
  • Experience with agentic AI systems, agent frameworks, and agent performance and reliability evaluation
  • Strong algorithm development experience
  • Knowledge of model distillation, quantization, and pruning
  • Knowledge of zero-shot, few-shot, self-supervised, unsupervised learning, and generative AI models for synthetic data creation
  • Experience fine-tuning or training large language models
  • Strong software development experience
  • Familiarity with GPU technologies including CUDA, cuDNN, and TensorRT
  • Experience with data processing and storage tools
  • Security and networking background, including security protocols, network architectures, firewalls, and intrusion detection systems

NVIDIA Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.

  • Equity Value & Accessibility Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
  • Healthcare Strength Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
  • Retirement Support Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.

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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 1999 sparked 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 — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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