Remote LLM Data Scientist & AI Algorithm Engineer

Binance; Hong Kong; Remoto; HKD 942.000 - 1.648.000; Tempo pieno

Vantaggi offerti da questo lavoro

Remote-first, work-from-home

Competitive salary and benefits

Career growth and continuous learning

Flat structure and world-class talent

Descrizione del lavoro

Binance seeks a highly skilled AI professional to advance through innovative AI solutions, focusing on developing and refining Large Language Models (LLMs) to extract actionable insights, improve business decision‑making, and optimize prompt design for accurate outputs. The role involves creating scalable LLM/RAG frameworks tailored to customer service scheduling, with a remote-first setup.

The candidate will implement end-to-end pipelines, collaborate with product and CS teams, and stay ahead

Competenze

• 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.

Mansioni

• Own the full LLM pipeline from data preparation to production real case usage.
• Design, iterate and optimize prompts to maximize model utility and safety across products and languages.
• Build and maintain RAG QA/search systems connected to multi-source knowledge bases.
• Familiar with vLLM/SGLang inference architectures and deploying LLM services on multi-GPU or clusters.
• Design, implement and operate multi-agent LLM architectures including task decomposition and tool-calling workflows.
• Develop evaluation pipelines to measure prompt and model quality, bias, and hallucination rates.
• Collaborate with product and CS teams to integrate AI models into conversational Chatbot scenarios.
• Track cutting-edge research and author tech blogs to improve current architecture.

Conoscenze

Deep learning

NLP

Prompt engineering

LLM workflows

English & Chinese

Formazione

Master’s degree or higher in Computer Science

Descrizione del lavoro

Binance seeks a highly skilled AI professional to advance through innovative AI solutions, focusing on developing and refining Large Language Models (LLMs) to extract actionable insights, improve business decision‑making, and optimize prompt design for accurate outputs. The role involves creating scalable LLM/RAG frameworks tailored to customer service scheduling, with a remote-first setup.

The candidate will implement end-to-end pipelines, collaborate with product and CS teams, and stay ahead