Senior Security Architect – AI, ML

5 hours ago

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NVIDIA

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Artificial Intelligence • Gaming • Automotive

NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.

10,000+ employees

Founded 1993

🤖 Artificial Intelligence

🎮 Gaming

📋 Description

• Help define the field of ML/AI security architecture. • Research, define, design, advise, develop, review, and implement architecture solutions meeting internal and external security requirements and standards. • Collaborate across the company to guide the direction of designing secure AI and ML products, working with hardware, software, research, IT, and product teams. • Architectural modeling, validation, definition, following standards bodies, and developing infrastructure enabling trusted platforms using hardware security methods. • Perform Product Cybersecurity assessments on projects of multiple NVIDIA product lines. • Complete independent reviews on project work packages that are AI and ML specific. • Develop new attacks and defenses for ML/AI enabled applications. • Support the development of the Product Cybersecurity Training strategy and deliver cybersecurity trainings to increase awareness and understanding of security requirements, tools, processes, and technical standards for NVIDIA ML/AI systems.

🎯 Requirements

• MS or PhD in Electrical Engineering, Computer Science, Computer Engineering, Artificial Intelligence, Data Science, Mathematics, Statistics, or equivalent experience. • 8+ years of relevant work experience. • First-hand work with Machine Learning, Deep-Learning, or Artificial Intelligence. • Familiarity with current attacks on ML models, including adversarial examples, training data extraction, model extraction, and data poisoning. • Background with attacks on and attack surface of LLM-powered systems, including direct and indirect prompt injection, guardrail evasion, and tool abuse. • Experience using modern Deep Learning software architectures and frameworks like Jax or PyTorch. • Experience with security development lifecycle processes and tools. • Programming and debugging fundamentals across languages such as Python, C/C++.

🏖️ Benefits

• Health insurance • Retirement plans • Paid time off • Professional development