LLM Data Scientist/Algorithm Engineer (Top Talent Program)

Binance; Sydney; Remote; AUD 140,000 - 210,000; Full time

Benefits offered by this job

Work-from-home arrangement

Competitive salary

Job summary

Binance is seeking an LLM Data Scientist/Algorithm Engineer for its Top Talent Program. This 100% remote role focuses on developing and refining large language models to extract actionable insights, optimize prompts, and build scalable LLM/RAG frameworks for customer service.

You’ll own the end-to-end pipeline from data prep to production and work with multilingual teams. The role requires a Master’s or higher in CS/Data Science, at least 2 years of deep-learning/NLP experience including 1+ year

Qualifications

• Master’s degree or higher in Computer Science, Data Science or related field.
• At least 2 years of deep-learning/NLP experience with 1+ year practical LLM work.
• Demonstrated prompt engineering expertise (few-shot design, prompting, tuning).
• Experience deploying and operating LLM services on multi-GPU or cluster environments.
• Proficiency in English and Chinese for cross-team collaboration.

Responsibilities

• Own the full LLM pipeline from data prep to production real-case usage.
• Design, iterate and optimize prompts to maximize model utility and safety across products and languages.
• Build and maintain Retrieval-Augmented Generation (RAG) QA/search systems linking multi-source knowledge bases.
• Design and operate multi-agent LLM architectures including task decomposition and tool-calling workflows.
• Develop evaluation pipelines (automatic metrics and human feedback) to measure quality, bias and hallucination rates.
• Collaborate with product and CS teams to integrate AI models into conversational chatbots across scenarios.
• Track research and publish technical blogs; improve current architecture.

Skills

LLMs

NLP

Prompt engineering

RAG

Multi-agent LLM workflows

English & Chinese communication

Education

Master’s degree or higher in Computer Science or Data Science

Tools

vLLM

SGLang

LangGraph

CrewAI

AutoGen

Job description

LLM Data Scientist/Algorithm Engineer (Top Talent Program)

Full-time: Remote /

Remote

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, Web3 features, and more. We leverage the power of digital assets and blockchain to build an inclusive financial ecosystem to advance the freedom of money and improve 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.

• 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 Chatbotin differentscenarios.
• Track cutting-edge research, author tech blogs, and keep improve current architecture.
• 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 with the world’s leading blockchain ecosystem
• Collaborate with world-class talent in a user-centric global organization with a flat structure
• Tackle unique, fast-paced projects with autonomy in an innovative environment
• Thrive in a results-driven workplace with opportunities for career growth and continuous learning
• Competitive salary and company benefits
• Work-from-home arrangement (the arrangement may vary depending on the work nature of the business team)

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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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.