Description
As a Senior Deep Learning Solution Architect at NVIDIA, you will contribute to the development of open-source inference frameworks, develop and optimize KV cache offloading frameworks, drive R&D on compute performance in distributed training, and study computational challenges in machine learning systems.
Responsibilities:
- Contribute to the development of open-source inference frameworks such as SGLang and vLLM
- Develop and optimize KV cache offloading frameworks for LLM workloads
- Drive R&D on compute performance in distributed training
- Study computational challenges in machine learning systems
Requirements:
- Master's degree or above in computer science, mathematics, electrical engineering, automation, or related fields
- Over 5 years working experience in the technology industry
- Strong interest in accelerated computing, parallel computing, and heterogeneous computing
- Solid programming skills, with a good understanding of data structures and computer systems fundamentals
Nice to Have:
- Familiarity with heterogeneous computing, distributed training, parallel computing
- Experience in performance analysis, performance modeling, or performance optimization
- Strong ability to define new problems and explore solutions
- Proficiency with AI coding tools
We offer competitive salaries and a generous benefits package.
This listing is enriched and indexed by YubHub. To apply, use the employer's original posting:
https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCareerSite/job/China-Beijing/Senior-Deep-Learning-Solution-Architect_JR2024045