Principal Developer, AI Networking

🕒 June 12

🏄 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 26%

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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

• Characterizing AI workloads and deep learning models aimed at large-scale LLM training and inference on NVIDIA supercomputers. • The role centers on distributed systems with a focus on high-performance networking and NVIDIA communication libraries. • Benchmarking, profiling, and analyzing the performance to find bottlenecks and identify areas for improvement and optimizations, with a strong emphasis on networking aspects. • Developing PyTorch trace-based profiling, analysis, and replaying toolset to aid in benchmarking, debugging, and co-designing network systems for LLM workloads. • Collaborating with multiple teams from hardware to software to provide performance analysis insights. • Defining performance test plans, setting performance expectations for new technologies and solutions, and working to achieve performance targets.

🎯 Requirements

• B.Sc in Computer Science or Software Engineering or equivalent experience. • 15+ years of experience with high-performance networking (RDMA, MPI, NCCL, SHARP). • Demonstrated ability in performance evaluation techniques and approaches. • Experience with NVIDIA GPUs and the CUDA library. • Knowledge of deep learning frameworks like TensorFlow or PyTorch. • Expertise in networking collective communication libraries such as NCCL and protocols like RoCE and RDMA. • Fast and self-learning capabilities with strong analytical and problem-solving skills. • Proficiency in programming languages: Python, Bash, and C++. • Experience with a container-based development environment. • Great teammate who communicates clearly and works well with others.

🏖️ Benefits

• equity • benefits

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