Responsibilities
1. Build tools and platforms related to large language models, including backend R&D of large language models, plug-ins, workflows, agents, evaluation, security, SFT and other related platforms. Cross-departmental teams work closely together to promote the development of the core architecture and ecosystem of large models 2. Design large language model solutions for various business scenarios, and support business scenarios such as LLMOPS and RAG knowledge base support large model product iteration with high efficiency and high standards, have a deep understanding of the business, and can self-drive business growth with technology 3. Be responsible for the online performance optimization and stability assurance of large models. In terms of performance, you can explore the performance bottlenecks of the system from multiple perspectives and constantly challenge the limits in terms of stability, ensure high SLA of the product, and at the same time provide degradation guarantees for the entire system 4. Design highly scalable tools, platforms and solutions to greatly improve construction and deployment efficiency to support rapid business growth 5. Pay attention to the back-end and cutting-edge technologies of large models, follow up on the latest research progress and application trends in the industry, and propose innovative ideas and directions.
Qualifications
1. Bachelor degree or above, computer-related major, more than 3 years of back-end development experience 2. Familiar with the basic principles of computer architecture, data structure and algorithm, operating system, database, network, etc. 3. Familiar with Golang or at least one type of back-end programming language (Python/Java/C++, etc.) 4. Experience in distributed software architecture design, development and operation and maintenance, and the ability to quickly locate and debug problems 5. Have good coding habits to ensure the output of high-quality software 6. Excellent communication and collaboration skills, analytical problem-solving skills and learning ability. Bonus points: 1. Familiar with the development of large model applications, such as familiar with LangChain, LlamaIndex and other frameworks, those with experience in prompt word engineering and LLM Agent development are preferred 2. Familiar with Docker, Kubernetes, have a strong interest in cloud computing and container technology, and those who are familiar with the CNCF ecosystem are preferred.
