Data Scientist (LLM), Multi-Agent Systems

About the Role

This role sits at the intersection of quantitative finance, machine learning, and natural-language understanding. You’ll leverage NLU techniques—like sentiment and intent analysis—to mine news and social media for trading signals, build and mathematically refine predictive models, and rigorously backtest and optimize your strategies to drive data-driven investment decisions.

Responsibilities

• Responsible for the architecture design and core module development of LLM-based AI Agent systems, including task planning, memory management, tool invocation, and workflow execution;
• Lead the development of a general-purpose Agent platform capable of multi-task coordination and multi-agent collaboration, enhancing the usability and stability of large models in complex business scenarios;
• Leverage key technologies such as LLMs, RAG, vector search, and function calling to build intelligent systems with contextual understanding and knowledge injection capabilities;
• Develop evaluation systems and automated testing tools for Agent behavior to continuously optimize task completion rate, response quality, and reliability;
• Drive the application of AI Agents in vertical scenarios such as search, trading, deep analysis, and automated data engineering to unlock the full value of LLMs.

Requirements

Why Binance

Binance is committed to being an equal opportunity employer. We believe that having a diverse workforce is fundamental to our success.

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