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Senior Deep Learning Solution Architect

NVIDIA· Architect, Solutions
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Beijing, ShanghaiFull-timePosted 1mo ago

About the role

Senior-level architect focused on bringing NVIDIA’s AI computing technology to various industries, with emphasis on LLM inference/training acceleration, distributed training performance, and optimization of AI/HPC workflows.

Responsibilities

  • Contribute to development of open-source inference frameworks (e.g., SGLang, vLLM) including feature and operator development, performance optimization, and model support in collaboration with the community.
  • Develop and optimize KV cache offloading frameworks for LLM workloads, enabling multi-level cache offloading and reuse across CPU, SSD, and remote storage to improve inference efficiency (Team project: FlexKV).
  • Drive R&D on compute performance in distributed training and explore methods and technologies for performance optimization.
  • Study computational challenges in machine learning systems, identify common needs and bottlenecks, and build example code, acceleration libraries, or frameworks accordingly.

Qualifications

  • Over 5 years of experience in technology industry.
  • Master’s degree or above in computer science, mathematics, electrical engineering, automation, or related fields.
  • Strong interest in accelerated computing, parallel computing, and heterogeneous computing with motivation to explore deeply.
  • Solid programming skills with a good understanding of data structures and computer systems fundamentals.
  • Strong learning agility, adaptability, and ability to analyze, define, and independently explore technical problems.

Skills

Required:Open-source framework developmentKV cache offloadingDistributed training performance optimizationProblem solving and independent exploration

Benefits

  • Competitive salaries
  • Generous benefits package
Last updated Aug 28, 2026. Interested? Apply on the company site.

About NVIDIA

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NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.

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