英伟达Systems Infrastructure Software Engineer
任职要求
The NVIDIA Infrastructure Group is seeking world-class programmers to design, implement, and debug the next generation of large-scale, general-purpose graphics and computing chips. In this role, you will help build the core verification infrastructure that drives the development of our GPU and Tegra chips.This strongly object-oriented C++ and Python infrastructure encompasses several extensive applications that allow us to efficiently verify the world's largest chips with a sophisticated distributed computing execution and triage environment. Come and join our diverse, international, fast-paced team with high production-quality standards.
What You’ll Be Doing:
• Developing environments to program and test next-generation GPU and SoC features well before they are integrated into products or supported by driver software. Every day brings new and meaningful challenges.
• Collaborating with colleagues across architec…工作职责
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• Design, develop, and improve scalable infrastructure to support the next generation of AI applications, including copilots and agentic tools. • Drive improvements in architecture, performance, and reliability, enabling teams to bring to bear LLMs and advanced agent frameworks at scale. • Collaborate across hardware, software, and research teams, mentoring and supporting peers while encouraging best engineering practices and a culture of technical excellence. • Stay informed of the latest advancements in AI infrastructure and contribute to continuous innovation across the organization.
• Architect, develop, and maintain Python-based tools and services to efficiently run a performance-focused multi-tenant Linux cluster including embedded, desktop, and server systems • Work with industry standard tools (Kubernetes, Slurm, Ansible, Gitlab, Artifactory, Jira) • Actively support users doing development, functional testing, and performance testing on current and pre-production GPU cluster systems • Work with various teams at NVIDIA across different timezones to incorporate and influence the latest tools for operating GPU clusters • Collaborate with users and system administrators to seek out ways to improve UX and operational efficiency • Become an expert on the entire AI infrastructure stack
• Designing and developing software for testing and analysis of our codebases • Building scalable automation for build, test, integration, and release processes for publicly distributed deep learning libraries • Developing throughout the software stack, from the user experience and user interfaces down to the cluster and database layers • Configuring, maintaining, and building upon deployments of industry-standard tools (e.g. Kubernetes, Jenkins, Docker, CMake, Gitlab, Jira, etc.) • Develop front-end solutions using HTML, CSS, JavaScript, and related web technologies • Advancing the state of the art in those industry-standard tools