LLM Data Scientist/Algorithm Engineer (Fully Remote)

Overview Join Binance to advance AI-powered scheduling optimization for customer service. You will own end-to-end LLM pipelines and deploy multi-source QA systems in a fast-growing blockchain ecosystem. You’ll shape prompts, build RAG-based solutions, and deploy multi-agent LLM workflows that scale across languages and products. This role offers hands-on experimentation with cutting-edge AI, strong collaboration with product and CS teams, and opportunities to influence how AI informs business decisions. Leistungen / Benefits Work-from-home arrangement competitive salary and company benefits opportunities for career growth and continuous learning flat organizational structure dynamic, innovative environment global team collaboration Verantwortungsbereiche Own the full LLM pipeline from data preparation to production usage.

Design, iterate and optimize prompts for multiple languages and contexts. Build and maintain RAG QA/search systems connected to multi-source knowledge bases. Deploy and operate LLM services on multi-GPU or cluster environments. Design and operate multi-agent LLM architectures including task decomposition and tool-calling workflows. Develop evaluation pipelines to measure prompt and model quality, bias, and hallucinations. Collaborate with product and CS teams to integrate AI models into conversational chatbot scenarios. Track research, author tech blogs, and improve current architecture. Zentrale Anforderungen 2+ years of deep-learning/NLP experience, including 1+ year practical LLM work (SFT, DPO, RAG, etc.). Master’s degree or higher in Computer Science, Data Science or related field.

Demonstrated prompt engineering and tuning expertise (few-shot design, structured prompting, tuning, safety). Experience building and deploying multi-agent LLM workflows with agent orchestration and memory sharing. Strong coding ability, good English communication, and rapid learning mindset. Good communication self-motivated and ownership curiosity about AI technologies LLM/ NLP Prompt engineering