Description
We are seeking a Senior Deep Learning Solution Architect to 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.
The ideal candidate will have over 5 years of working experience in the technology industry, a master's degree or above in computer science, mathematics, electrical engineering, automation, or related fields, and strong interest in accelerated computing, parallel computing, and heterogeneous computing.
Responsibilities:
- 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.
- 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.
Requirements:
- 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!