LLM Data Scientist/Algorithm Engineer (Top Talent Program)

About the Position

Binance is a leading global blockchain ecosystem behind the world’s largest cryptocurrency exchange by trading volume and registered users. We are trusted by 300+ million people in 100+ countries for our industry-leading security, user fund transparency, trading engine speed, deep liquidity, and an unmatched portfolio of digital-asset products. Binance offerings range from trading and finance to education, research, payments, institutional services, and more. Our mission is to increase the freedom of money and financial access for people around the world.

We are seeking a highly skilled professional to join our team, focusing on advancing through innovative AI solutions.

The successful candidate will develop and refine Large Language Models (LLMs) to extract actionable insights, improve business decision-making, and optimize prompt design for more accurate outputs. Additionally, the role includes creating scalable and robust LLM/RAG frameworks tailored to customer service scheduling, fostering innovation and maintaining a competitive market edge.

This role is 100% Remote, Work from Home based.

Responsibilities

• Own the full LLM pipeline from data preparation to production real case usage.
• Design, iterate and optimize prompts (zero-/few-shot, chain-of-thought, tool-calling, etc.) to maximize model utility and safety across products and languages.
• Build and maintain Retrieval-Augmented Generation (RAG) QA/search systems that connect to multi-source knowledge bases.
• Familiar with vLLM/SGLang inference architectures and have proven experience deploying and operating LLM services on multi-GPU or cluster environments.
• Design, implement and operate multi-agent LLM architectures (e.g. LangGraph, CrewAI, AutoGen) including task decomposition, agent orchestration, memory sharing and tool-calling workflows.
• Develop evaluation pipelines (automatic metrics & human feedback) to measure prompt and model quality, bias, and hallucination rates.
• Collaborate with product and CS teams to integrate AI models into conversational Chatbot in different scenarios.
• Track cutting-edge research, author tech blogs, and keep improving current architecture.

Requirements

• Master’s Degree or higher in Computer Science, Data Science or related field.
• At least 2 years of deep-learning/NLP experience, including 1+ year practical LLM work (SFT, DPO, RAG, quantization, inference optimization, etc.).
• Demonstrated prompt engineering & tuning expertise (few-shot design, structured prompting, prefix-/p-tuning, reward re-ranking, safety filtering).
• Practical experience building and deploying multi-agent LLM workflows, with understanding of agent-orchestrator patterns, shared memory, long-horizon planning and guard-rail design.
• Proficient in both English and Chinese communication for efficient cross team collaboration.

We Offer

• Shape the future of finance
• Collaborate with world-class talent in a user-centric global organization with a flat structure
• Tackle challenging projects in a fast-paced and innovative environment with autonomy
• Thrive in a results-driven workplace with opportunities for career growth and continuous learning
• Competitive salary and company benefits
• Remote-first, work-from-home arrangement (may vary depending on the nature of the role and team)

About the Company

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

By submitting a job application, you acknowledge that you have read our Candidate Privacy Notice.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.