LLM Data Scientist/Algorithm Engineer (AI)

TL;DR

LLM Data Scientist/Algorithm Engineer (AI): Developing and refining Large Language Models and RAG frameworks to extract business insights and optimize customer service scheduling with an accent on prompt design and scalable AI architectures. Focus on building multi-agent LLM workflows, optimizing inference architectures, and implementing rigorous evaluation pipelines to reduce hallucinations.

Location: Remote (Must be based in Asia)

Company

Leading global blockchain ecosystem and the world’s largest cryptocurrency exchange.

What you will do

• Own the full LLM pipeline from data preparation to production real-case usage.
• Design and optimize prompts (zero-/few-shot, chain-of-thought, tool-calling) to maximize model utility and safety.
• Build and maintain Retrieval-Augmented Generation (RAG) QA/search systems connected to multi-source knowledge bases.
• Implement and operate multi-agent LLM architectures using tools like LangGraph, CrewAI, and AutoGen.
• Develop evaluation pipelines using 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.

Requirements

• Master’s Degree or higher in Computer Science, Data Science, or a related field.
• At least 2 years of deep-learning/NLP experience, including 1+ year of practical LLM work (SFT, DPO, RAG, quantization).
• Expertise in prompt engineering, tuning, and safety filtering.
• Experience deploying LLM services on multi-GPU or cluster environments with vLLM/SGLang.
• Proficient in both English and Chinese communication.
• Must be based in Asia.

Nice to have

• Experience with inference optimization.
• Ability to author technical blogs and track cutting-edge AI research.

Culture & Benefits

• 100% work-from-home arrangement.
• Collaboration with world-class talent in a flat, user-centric global organization.
• High autonomy in a fast-paced, results-driven innovative environment.
• Competitive salary and company benefits.
• Opportunities for continuous learning and career growth.