המקום בו המומחים והחברות הטובות ביותר נפגשים
What you will be doing:
Evaluate and run multi-node jobs on large clusters to assess performance and developer experience in distributed deep learning environments.
Understand and profile workloads for deep learning applications. Educate customers and tech press to run these workloads and benchmark NVIDIA data center systems for performance evaluations.
Conduct performance benchmarking of AI infrastructure with industry-standard models and frameworks (e.g., vLLM, PyTorch, TensorFlow) to measure throughput, latency, and scalability.
Engage with various teams across NVIDIA such as product, marketing, hardware, software engineering, and QA to improve NVIDIA's product offerings.
Develop developer-focused content, including detailed tutorials and code samples, to demonstrate the latest features in NVIDIA’s tools and libraries.
Write technical whitepapers, product briefs, and solution blueprints to highlight innovative use cases, architecture designs, and best practices in AI infrastructure.
Deliver live demos and technical presentations at leading industry events, such as the NVIDIA GPU Technology Conference (GTC), CES, SIGGRAPH, and other global conferences, showcasing cutting-edge NVIDIA technologies.
A Bachelor’s or Master’s in Software Engineering, Computer Science, Computer Engineering, Electrical Engineering or equivalent experience.
5+ years of experience.
Proficiency in Python and C++ for AI and HPC applications.
Experience using large scale multi node GPU infrastructure on premise or in CSPs
Background in deep learning model architectures and experience with Pytorch and large scale distributed training
Deep understanding of computer architecture, and familiarity with the fundamentals of GPU architecture. Experience with NVIDIA's Infrastructure and software stacks.
Demonstrate proficiency in managing job scheduling, workload orchestration, and deploying multi-node GPU clusters using Slurm and Kubernetes.
Solid understanding of network protocols, distributed system communication, and high-speed interconnects (e.g., InfiniBand, RDMA, Ethernet) to optimize data flow across nodes in HPC environments.
Hands-on experience with NVIDIA GPUs, HPC storage, networking, and cloud computing.
You will also be eligible for equity and .
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