Software Engineer, AI Networking Architect

Job Requisition ID

JR2018966

Job Category

Engineering

Time Type

Full time

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.
  
  

• B.Sc. Or M.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.
  
  

• 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.