Senior Deep Learning Communication Architect
Description For Senior Deep Learning Communication Architect
NVIDIA, a global leader in accelerated computing and AI technology, is seeking a Senior Deep Learning Communication Architect to join their innovative team. This role sits at the intersection of deep learning and distributed systems, focusing on scaling DNN models and optimizing communication performance for massive-scale deployments.
The position offers a unique opportunity to work on cutting-edge technology that powers the next generation of AI systems. You'll be responsible for designing and implementing communication protocols that enable efficient distributed deep learning training and inference across systems with hundreds of thousands of nodes. This involves working with state-of-the-art hardware and software technologies, including NVLink, InfiniBand, and various deep learning frameworks.
The ideal candidate brings strong technical expertise in both deep learning and distributed systems, with 6+ years of relevant experience. You'll need deep understanding of parallelism techniques, including Data Parallelism, Pipeline Parallelism, and Tensor Parallelism, along with practical experience in optimizing LLM training and inference performance.
NVIDIA offers a competitive compensation package with a base salary range of $184,000 - $356,500 USD (depending on level), plus equity and comprehensive benefits. The company is known for its innovative culture and commitment to pushing technological boundaries. You'll be joining a team that's at the forefront of AI innovation, working on technology that's transforming industries and society.
This role presents an excellent opportunity for someone passionate about deep learning and distributed systems to make a significant impact on the future of AI computing. You'll be working with some of the industry's brightest minds in an environment that encourages innovation and technical excellence.
Responsibilities For Senior Deep Learning Communication Architect
- Optimize communication performance by identifying and eliminating bottlenecks in data transfer and synchronization
- Design and implement communication protocols for deep learning workloads
- Collaborate with hardware and software teams on high-speed interconnects
- Research and evaluate new communication technologies
- Build proofs-of-concept and conduct experiments
- Scale DNN models and training/inference frameworks to systems with hundreds of thousands of nodes
Requirements For Senior Deep Learning Communication Architect
- Ph.D., Masters, or BS in Computer Science, Electrical Engineering, or related field
- 6+ years experience in Building DNNs, Scaling of DNNs, and DNN frameworks
- Experience in evaluating and optimizing LLM training and inference performance
- Deep understanding of parallelism techniques
- Understanding of emerging serving architectures
- Proficiency in DNN training and Inference frameworks
- Strong programming skills in C++ and Python
- Familiarity with GPU computing, CUDA, OpenCL, InfiniBand and RoCE networks
Benefits For Senior Deep Learning Communication Architect
- Equity
- Medical Insurance
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