Binance - Accelerator Program - LLM Model Training & Data Processing

• Assist in the training, fine-tuning, and evaluation of Large Language Models (LLMs) using public and in-house datasets. • Support the development and optimization of AI agents, including prompt engineering, memory modules, planning strategies, and integration with external tools. • Design, implement, and manage data annotation pipelines, including schema definition, labeling guidelines, and quality control processes. • Work closely with research and engineering teams to improve model performance, scalability, and robustness. • Conduct experiments, perform data analysis, and clearly document methodologies and findings. • Explore and test new tools, frameworks, and best practices for enhancing LLM systems and AI agent capabilities. • Currently pursuing or recently completed a Degree in Computer Science, Artificial Intelligence, Electrical Engineering, or a related discipline. PHD is Bonus. • Solid understanding of machine learning and deep learning fundamentals. • Familiarity with transformer models, LLMs (e.g., LLaMA, Qwen), or related technologies is a strong plus. • Experience or interest in prompt engineering, fine-tuning methods (e.g., LoRA, QLoRA), and model evaluation techniques. • Basic knowledge of data annotation workflows and labeling tools. • Strong analytical and problem-solving skills; able to work both independently and collaboratively. • Fluency in English is required to be able to coordinate with overseas partners and stakeholders. Additional languages would be an advantage.