Large Language Model Algorithm Engineer

Job Description:

• The construction of large language model Agents technology and its application in Shopee e-commerce, using retrieval-augmented(RAG) technology in business fields such as chatbot, videos, search and recommendation, etc.
• Exploration and implementation of the core algorithms of large language models, including ultra-large-scale pre-training, instruction fine-tuning, reinforcement learning, etc., from a multilingual perspective to solve problems such as hallucinations and long texts etc
• Optimize the inference speed of language models, explore and implement acceleration strategies such as Medusa, Speculative Decoding, multi-LoRA inference, and Pruning, and build an inference framework for LLMs.
• Establish a complete large model evaluation system, provide standardized model evaluation capabilities, establish and improve evaluation data sets, and use model evaluation to reversely drive and improve the performance of large language models in actual business.
• Data algorithm of Large language model involving construction of multi-language pre-training, instruction fine-tuning, human preference behavior and other data systems, establishing a complete engineering system for model fine-tuning and data set preparation, effectively improving data set quality and delivery capabilities.

Requirements:

• Excellent coding skills, data structure and basic algorithm skills, proficiency in Python/Pytorch coding, and harness the Hands-on ability.
• Those who are familiar with NLP and CV related algorithms and technologies, and those who are familiar with large model training and RL algorithms are preferred
• Familiar with the basic principles and training methods of industry-leading LLM (such as GPT, LLaMA), or familiar with the basic principles and training methods of mainstream multi-modal large models (such as Flamingo, LLaVA), and have research experience in text generation or dialogue systems, etc.
• Excellent problem analysis and solving skills, able to deeply solve problems in large model training and application
• Good communication and collaboration skills, able to explore new technologies with the team and promote technological progress.