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NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 fueled the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI and enabled the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that matter to the world, and that only we can tackle. This is our life’s work, to amplify human imagination and intelligence, and expand what is possible. Make the choice to join us today.
As a software engineer in our internal infrastructure group, you will craft services, tools and libraries for enhancing engineering productivity of our teams with the goal of enabling security and compliance of our IP with minimal customer effort. This will help secure workflows for worldwide chip development, verification, and artificial intelligence. You will continuously innovate and develop scalable, reliable, best in class systems and tools to enable the next generation of chips in collaboration with the best engineers in the world at NVIDIA!
Design and implement new services, tools and libraries to make our customers' workflows "Secure By Default".
Be responsible for the complete lifecycle from architecture to production deployment of security tooling.
Partner with chip design, security and AI teams to understand complex workflows and translate their requirements into technical software solutions.
Directly contribute to the overall quality of and improve time to market for our next generation chips and deep learning models.
Proficiency developing and deploying Python systems in a Linux environment.
Proven strong foundation in object-oriented design and software architecture patterns.
8+ years of hands-on experience with CI/CD pipelines (GitLab, GitHub, or Perforce) and DevOps practices.
Consistent track record of owning features end-to-end including testing, deployment, and monitoring.
Excellent planning, interpersonal and problem solving skills.
Flexibility/adaptability working in a dynamic environment with unique challenges and requirements.
A passion for improving the efficiency and effectiveness of other specialists and engineers.
BS/MS in Computer Science/Engineering or equivalent experience with 5+ years experience using those skills.
Expertise in Python backends (FastAPI, Django, or Flask) with production-scale deployments
Cloud-native infrastructure experience: Kubernetes orchestration, microservices architecture, and observability (OpenTelemetry)
Knowledge of databases, data lakes, and operating on large data sets (MongoDB, OpenSearch, PostgreSQL)
Familiarity with Export Control Compliance or IP Security
Experience with EDA tools, chip design workflows, or ML infrastructure
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