Senior Software Engineer - AI Security Engineering

November 1

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NVIDIA

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GPU-accelerated computing • artificial intelligence • deep learning • virtual reality • gaming

10,000+ employees

Founded 1993

🤖 Artificial Intelligence

🎮 Gaming

Description

• Lead security initiatives to integrate comprehensive security solutions across the AI product lifecycle. • Develop and deliver sophisticated software applications and platforms that enable NVIDIA to release AI products securely and attest details about the release in the form of a bill of materials. • Directly engage product teams and partner security teams to determine opportunities to improve our security posture. • Work closely with customers, partners, and team members to gather requirements, set priorities, and manage expectations throughout the project lifecycle. • Work within various Release Pipeline teams to automate security scanning to assess release readiness for different NVIDIA platforms.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Cybersecurity, AI, or a related field (or equivalent experience) • 5+ years of confirmed software development engineering or development operations capabilities in build or standup highly scalable low latency end to end applications, infrastructure, and automation frameworks at large scale. • Hands-on experience identifying vulnerabilities and implementing security measures for AI systems in production environments • Experience in full-stack design and development, with a focus on microservice architecture platforms. • Expected to have a working knowledge of HTML5, CSS, and JavaScript and a basic understanding of user interface and user experience (UI/UX) design • Background with modern front-end frameworks Angular or React • Knowledgeable in implementing object-oriented languages in distributed environments, including Python/Golang and RESTful APIs • Experience designing reports from scalable databases or datastores (MySQL, noSQL db or equivalent SQL technology) • Familiarity with industry-standard tools for queuing, caching, and document databases, including Redis, RabbitMQ, and Elasticsearch. • Familiarity with deploying to cloud technologies and infrastructure • Familiarity with tools like Figma to create wireframes and mock-ups, then translating these designs into reusable code and building high-quality UI components with a focus on scalability. • Proficiency in working with scalable, high-availability, and low-latency systems (Kubernetes and Docker) • Understanding of Dependency Managers • Experience in integration of solutions in build pipelines

Benefits

• Equity and benefits