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AI Networking Architect
·Israel
Not specifiedFull-timeAI EngineeringComputer Hardware
Join a multidisciplinary team to model and optimize AI workloads for advanced computing platforms. Analyze distributed training, inference, and LLMs to define networking architecture requirements, build simulations and analytical tools, and influence product roadmaps.
Responsibilities
- Model performance of complex AI workloads to identify bottlenecks and recommend optimizations.
- Analyze new AI models, distributed training, and inference workloads to understand infrastructure needs.
- Build platforms, simulations, and analytical tools to evaluate compute, memory, storage, and network trade-offs.
- Translate research insights into software, hardware, and networking architecture requirements.
- Partner with architecture, software, and product teams to shape NVIDIA's networking and AI infrastructure roadmaps.
- Drive architectural innovation through deep workload analysis of ML frameworks.
Requirements
- B.Sc. or M.Sc. in Computer Science, Computer Engineering, Electrical Engineering, or equivalent.
- 3+ years of relevant industry or research experience.
- Strong ML/data science background with hands-on LLMs, generative AI, or deep learning systems.
- Systems-level thinking to estimate end-to-end requirements across the AI stack.
- Ability to translate research and product requirements into clear software/hardware specs.
- Excellent research skills including academic paper digestion and independent hypothesis testing.
- Advanced programming for performance modeling, data analysis, and prototyping.
- Excellent communication of complex technical findings.
Nice to have
- Experience with distributed training, 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.