LLM Data Scientist/Algorithm Engineer (Top Talent Program) at Binance

About Binance

Binance is a leading global blockchain ecosystem behind the world's largest cryptocurrency exchange by trading volume and registered users. Trusted by over 300 million people across more than 100 countries, Binance is known for industry leading security, user fund transparency, trading engine speed, deep liquidity, and an unmatched portfolio of digital asset products. Offerings span trading and finance, education, research, payments, institutional services, and more. The mission is to increase the freedom of money and financial access for people around the world.

Role Overview

Binance is seeking a highly skilled professional to join the 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. The role also 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 shot, few shot, chain of thought, tool calling, and similar techniques) to maximize model utility and safety across products and languages.
• Build and maintain Retrieval Augmented Generation (RAG) QA and search systems that connect to multi source knowledge bases.
• Work with vLLM/SGLang inference architectures and bring proven experience deploying and operating LLM services on multi GPU or cluster environments.
• Design, implement and operate multi agent LLM architectures such as LangGraph, CrewAI, and AutoGen, including task decomposition, agent orchestration, memory sharing, and tool calling workflows.
• Develop evaluation pipelines using automatic metrics and human feedback to measure prompt and model quality, bias, and hallucination rates.
• Collaborate with product and customer service teams to integrate AI models into conversational chatbots in different scenarios.
• Track cutting edge research, author technical blogs, and continuously improve the current architecture.

Requirements

• Master's degree or higher in Computer Science, Data Science, or a related field.
• At least 2 years of deep learning or NLP experience, including 1 or more years of practical LLM work (SFT, DPO, RAG, quantization, inference optimization, and similar).
• Demonstrated prompt engineering and tuning expertise, including few shot design, structured prompting, prefix and p tuning, reward re ranking, and 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.
• Proficiency in both English and Chinese for efficient cross team collaboration.

Why Binance

• 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, which may vary depending on the nature of the role and team.

Equal Opportunity

Binance is committed to being an equal opportunity employer. The company believes that having a diverse workforce is fundamental to its success. By submitting a job application, candidates acknowledge that they have read the Candidate Privacy Notice. Binance 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 the recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans.