Senior Deep Learning Solution Architect at NVIDIA

Beijing, Beijing, China -

Full Time

Start Date

Immediate

Expiry Date

03 Jul, 26

Salary

0.0

Posted On

04 Apr, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Deep Learning, Solution Architecture, AI Computing, HPC, LLM Inference, Training Acceleration, Distributed Training, Performance Optimization, Heterogeneous Computing, Parallel Computing, Data Structures, Computer Systems, SGLang, vLLM, KV Cache Offloading, AI Coding Tools

Industry

Computer Hardware Manufacturing

Description

NVIDIA is leading company of AI computing. At NVIDIA, our employees are passionate about AI, HPC , VISUAL, GAMING. Our SA team is more focusing to bring NVIDIA new technology into difference industries. We help to design the architecture of AI computing platform, analysis the AI and HPC applications to deliver our value to customers, focusing on defining and solving computational challenges in LLM inference and training acceleration, as well as network communication and data transfer optimization. What You'll Be Doing: Contribute to the development of open-source inference frameworks such as SGLang and 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, supporting 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. What We Need to See: Over 5 years working experience in the technology industry, with 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 the motivation to explore these areas in depth. Solid programming skills, with a good understanding of data structures and computer systems fundamentals. Strong learning agility, adaptability, and the ability to analyze, define, and independently explore technical problems. Ways to Stand Out from the Crowd: Familiarity with heterogeneous computing, distributed training, parallel computing, or other areas related to high-performance computing. Experience in performance analysis, performance modeling, or performance optimization; contributions to open-source frameworks are a plus. Strong ability to define new problems and explore solutions; candidates with independent PhD-level research experience are preferred. Proficiency with AI coding tools. With competitive salaries and a generous benefits package, we are widely considered to be one of the world’s most desirable employers! We have some of the most forward-thinking and hardworking people in the world working for us and, due to outstanding growth, our best-in-class engineering teams are rapidly growing. If you're a creative and autonomous person with a real passion for technology, we want to hear from you. NVIDIA is the world leader in accelerated computing. NVIDIA pioneered accelerated computing to tackle challenges no one else can solve. Our work in AI and digital twins is transforming the world's largest industries and profoundly impacting society. Learn more about NVIDIA.

Responsibilities

The role involves designing AI computing platform architectures and optimizing LLM inference and training performance. You will contribute to open-source frameworks and develop solutions for distributed training and cache offloading.