LLM Applied Data Scientist (RAG/ NLP)

About the Position

We are seeking a highly skilled LLM Applied Data Scientist (RAG/ NLP) to join our team in Taiwan, Taipei, Hong Kong, or Australia, Brisbane. This role is 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.

Responsibilities

• Design, develop, and optimize data processing and retrieval pipelines for enterprise-level generative tasks and model training applications (Customer Service, Token Report, Web3 Domain Models). This includes embedding, reranking, context engineering, and query rewriting models.
• Research and evaluate advanced AI-native retrieval algorithms (e.g., low-latency, multimodal retrieval, hierarchical retrieval, GraphRAG) to strengthen large-scale LLM/VLM/Agentic AI capabilities in Binance products.
• Collaborate with infrastructure and application teams to integrate RAG pipelines into production systems, ensuring scalability, reliability, and measurable business impact.
• Develop and optimize retrieval and ranking pipelines (indexing, vector search, retrieval scoring, reranking) to improve user experience.
• Participate in LLM training and RAG system, staying current with techniques such as pre-training, SFT, and reinforcement learning, and apply them to retrieval and generation tasks.
• Apply NLP, CV, and multimodal methods to analyze user-generated content (classification, quality evaluation, trend detection, comment analysis).

Requirements

• Master’s in Information Retrieval, NLP, Machine Learning, Computer Vision, Multimodal Learning, or related fields.
• Proficient in PyTorch with strong coding skills in Python or C++.
• Strong communication skills, intellectual curiosity, and passion for lifelong learning. Able to identify opportunities and drive cutting-edge retrieval & RAG technologies into real-world applications.
• Solid theoretical foundation in information retrieval, NLP, and deep learning (experience with embeddings, reranking, query understanding preferred).
• Hands-on experience with RAG, vector databases, multimodal/graph retrieval, or large-scale AI systems.
• Strong engineering ability to translate research into scalable, production-level systems.
• Self-driven, able to own projects end-to-end (design → implementation → deployment).
• Publications in top-tier conferences/journals (NeurIPS, ICML, ACL, CVPR, SIGIR, KDD, WWW) are a plus; awards in ACM/ICPC or similar competitions preferred.

We Offer

• 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).

About the Company

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.