Leveraging knowledge of large-scale models and intelligent agents, participate in the design and development of a series of AI-powered financial trading agency skills based on Web3 data, and integrate them into practical systems.
Perform post-training of large-scale language models (SFT, RL, etc.) to enhance the model's ability to utilize Binance's internal trading skills.
Assist in building and maintaining benchmark datasets to evaluate the performance of AI systems, and assist in building and iterating workflow prototypes for financial AI agent systems.
Work closely with senior engineers to complete system design, integration, and deployment.

Currently pursuing or holding a Bachelor’s, Master’s, or Ph.D. degree in Computer Science, Artificial Intelligence, Financial Engineering, Automation, or a related field.
Hands-on experience with post-training techniques such as Supervised Fine-Tuning (SFT) and Reinforcement Learning (RLHF / RLAIF). Familiar with common fine-tuning and reinforcement learning frameworks, such as Llama Factory, Slime, Verl, and OpenRLHF.
Familiarity with at least one mainstream deep learning framework (PyTorch, TensorFlow) and common LLM training/evaluation toolkits (Hugging Face Transformers, DeepSpeed, vLLM, etc.).
Excellent communication skills and a strong willingness to learn quickly.
Able to commit at least 6 months, working 5 days a week.

Competitive salary and company benefits
Work-from-home arrangement (the arrangement may vary depending on the work nature of the business team)

Data Scientist – LLM, Trading

Key skills