Principal Architect, AI Networking

🕒 April 24

🏄 California, Colorado, +2 more states – Remote

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💵 $272k - $431.3k / year

⏰ Full Time

🔴 Lead

🤖 AI Engineer

🦅 H1B Visa Sponsor

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👻 Ghost score 36%

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Logo of NVIDIA

NVIDIA

10,000+ employees

Founded 1993

🏥 Healthcare

🏭 Manufacturing

🤖 Artificial Intelligence

Healthcare • Manufacturing • Artificial Intelligence

NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.

📋 Description

• Setting the long-term technical vision for distributed AI communication systems • Conducting original research and prototyping next-generation networking solutions • Driving hardware-software co-optimization with various technologies • Investigating fundamental bottlenecks in communication runtimes for large-scale AI workloads • Integrating networking capabilities into AI serving stacks • Publishing findings and representing NVIDIA in industry forums and standards bodies • Mentoring senior engineers across the organization

🎯 Requirements

• 15+ years in systems software and/or networking • Deep expertise in high-performance networking (InfiniBand, RoCE, RDMA, NVLink) • Communication libraries knowledge (e.g. NIXL, NCCL, UCX, MPI, NVSHMEM) • GPU accelerated systems experience • Proven track record of defining and delivering complex, cross-team technical initiatives • MS, PhD or equivalent in Computer Science, Computer Engineering, Electrical Engineering, or a related field • Deep understanding of computer architecture, memory hierarchies, DMA engines, and OS-level networking • Understanding of ML systems concepts (transformer architectures, KV cache mechanics, model parallelism, or distributed training and inference patterns) • Proficiency in programming languages such as C, C++, Rust and Python

🏖️ Benefits

• Competitive salaries • Comprehensive benefits package • Eligibility for equity

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