Software Engineer, AI Networking Architect

Overview

• NVIDIA is building the world’s most advanced AI computing platforms, powering breakthroughs in generative AI, large language models, and scientific discovery.
• Our accelerated computing technologies enable researchers, engineers, and enterprises to push the boundaries of what is possible with artificial intelligence.
• We are seeking an AI Networking Architect to join the Networking Research Group.
• This role will help bridge the gap between emerging tasks supported by advanced technologies and the data center infrastructure that powers them.
• In this role, you will work at the intersection of AI applications, distributed systems, networking hardware, and software architecture.
• You will join a focused team of multidisciplinary engineers driving AI workload optimization through deep application understanding, network analysis, and end-to-end systems thinking.
• Your insights will directly shape NVIDIA products across the full stack - from applications and software libraries to hardware architecture and physical design.
• What You’ll Be Doing: Model the performance of complex AI workloads to identify bottlenecks and recommend system-level optimizations.
• Analyze brand-new AI models, distributed training techniques, and inference workloads to understand their infrastructure requirements.
• Build Platforms, simulations and HW platforms, execute AI workloads and build analytical tools to evaluate trade-offs across compute, memory, storage, and network behavior.
• Translate research insights and workload behavior into actionable software, hardware, and networking architecture requirements.
• Partner with architecture, software, and product teams to influence future NVIDIA networking and AI infrastructure roadmaps.
• Drive architectural innovation by applying deep workload analysis to real-world advanced machine learning frameworks.
• What we need to see: B.Sc.
• in Computer Science, Computer Engineering, Electrical Engineering, or equivalent experience.
• 3+ years of relevant industry or research experience.
• Strong machine learning or data science background, with hands-on experience in LLMs, generative AI, or deep learning systems.
• Strong systems-level thinking, capable of estimating end-to-end requirements across the AI stack.
• Shown ability to translate research findings and product requirements into clear software and hardware specifications.
• Excellent research skills, including the ability to digest academic papers, self-learn new domains, and independently test hypotheses.
• Advanced programming skills for performance modeling, data analysis, and prototyping.
• Excellent communication skills, demonstrating proficiency in presenting complex technical findings clearly and confidently.
• Ways to Stand Out from the crowd: Experience with distributed training, distributed inference, or large-scale AI serving systems.
• Experience in Agentic programming, and AI tools Familiarity with GPU clusters, collective communication, storage systems, or AI networking bottlenecks.
• NVIDIA is home to some of the most innovative and dedicated professionals in the industry.
• We are committed to fostering a diverse work environment and are proud to be an equal-opportunity employer.