LLM Applied Data Scientist (RAG/NLP)

Location: Hong Kong or Singapore. Remote-first, work-from-home arrangement; availability may vary depending on the business team and role.

Company

Global blockchain ecosystem providing cryptocurrency trading, financial services, payments, education, research, and other digital-asset products.

What you will do

• Design, develop, and optimize data processing, retrieval, indexing, vector search, scoring, and reranking pipelines for enterprise generative AI applications.
• Research AI-native retrieval methods including low-latency, multimodal, hierarchical, and graph-based retrieval such as GraphRAG.
• Build and improve RAG pipelines, embeddings, query rewriting, context engineering, and ranking models for large-scale LLM, VLM, and agentic AI systems.
• Collaborate with infrastructure and application teams to integrate retrieval systems into production with scalability, reliability, and measurable business impact.
• Support LLM training across pre-training, supervised fine-tuning, reward modeling, and reinforcement learning stages.
• Apply NLP, computer vision, and multimodal methods to classify, evaluate, and analyze user-generated content.

Requirements

• Master’s degree in information retrieval, NLP, machine learning, computer vision, multimodal learning, or a related field.
• Strong PyTorch skills and programming ability in Python or C++.
• Solid theoretical foundation in information retrieval, NLP, and deep learning, including embeddings, reranking, and query understanding.
• Hands-on experience with RAG, vector databases, multimodal or graph retrieval, or large-scale AI systems.
• Ability to translate research into scalable production systems and own projects from design through deployment.
• Strong communication skills, intellectual curiosity, and interest in cutting-edge retrieval and RAG technologies.

Nice to have

• Publications in NeurIPS, ICML, ACL, CVPR, SIGIR, KDD, WWW, or similar top-tier venues.
• ACM/ICPC or comparable competition awards.

Culture & Benefits

• Work with a global, user-centric organization and a flat structure.
• Autonomy in fast-paced, innovative projects.
• Opportunities for career growth and continuous learning.
• Competitive salary and company benefits.
• Remote-first, work-from-home arrangement subject to the nature of the role and team.