Responsibilities
1. Responsible for the design and implementation of algorithms and solutions in the field of AIOps, including timing analysis, log mining, fault prediction, root cause correlation inference and intelligent decision-making, etc. 2. Explore the implementation of LLM x AIOps, including but not limited to anomaly detection, root cause location, stop-loss disaster recovery and other scenarios 3. Continue to follow up on LLM cutting-edge technology, open source solutions and their application in the field of AIOps.
Qualifications
1. Master degree or above in computer, NLP, mathematics or statistics related majors 2. Have study background or project experience in statistical analysis, data mining, machine learning and AI and other related fields 3. Have good programming thinking, the ability to implement stand-alone/distributed algorithm solutions, be proficient in at least one mainstream data analysis and algorithm implementation language (including R, Python, Go, Scala, etc.), and be able to quickly explore and implement new solutions 4. Be proficient in the algorithm principles of the industry's mainstream large language models (GPT, ChatGLM, LLaMA, etc.), fine-tuning strategies, Prompt projects, vector databases, LangChain and other application paradigms 5. Priority will be given to winners who publish papers at top international conferences or journals in related fields, or participate in relevant data mining/machine learning competitions 6. Excellent data sensitivity and business understanding skills, able to discover effective insights from complex business data.
