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此界面为简体中文。雇主发布的职位名称和描述保留原文,可能为英文。

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LLM Data Scientist/Algorithm Engineer (Top Talent Program)

Binance

远程工作

地点
Remote (Australia, Hong Kong, New Zealand, Singapore, Taiwan)
工作安排
Full Time
发布日期
2026年10月20日

申请前,请在雇主网站确认职位仍在招聘,并检查完整要求和条件。

职位描述

此界面为简体中文。雇主发布的职位名称和描述保留原文,可能为英文。

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 improve 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 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 enviornment 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) 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. Originally posted on Himalayas

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选择能够回应职位要求的真实经历,说明你的贡献,只使用能够证实的数字。遵循雇主的申请说明,并在提交前检查联系方式、文档内容和 PDF。

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求职常见问题

为什么有些职位使用英文?

职位名称和描述由招聘企业撰写。为避免改变招聘要求或工作条件,我们保留原文。操作界面和本指南使用简体中文。如果中文搜索没有结果,可以尝试使用职位发布语言中的名称或技能,例如“software engineer”。搜索词不会自动翻译,界面语言也不代表企业要求的申请语言。

远程职位是否允许从任何国家工作?

不一定。企业可能对居住国家、工作许可或工作时段有要求。请查看原始招聘页面中的具体条件。如果未说明,应先向企业确认,再判断能否从你所在的地区工作。“远程”标签本身并不代表没有地点限制。

搜索没有结果时应该怎么办?

尝试更通用的职位名称或单个技能,并逐一移除筛选条件。不同企业可能用不同名称描述相似工作。如果某个职位已经消失,请在企业招聘页面搜索其职位编号。扩大搜索范围不会让已经关闭的职位重新开放。

申请会通过 ResumizeAI 直接提交吗?

申请按钮会打开外部网站。请按照企业或招聘服务的说明,在该网站完成并确认提交。在 ResumizeAI 中准备简历并不等于已经申请职位。如果链接只打开企业网站,请先找到对应职位,再继续申请流程。

如何针对职位调整简历和求职信?

将招聘要求与能够解释清楚的项目、任务和成果联系起来。突出相关经历,不要添加未经实际掌握的技能或虚构成绩。在求职信中用具体例子说明申请动机,并遵守企业要求的语言和文件格式。提交前检查两份文件,确保内容准确、联系方式正确、链接可用。