Binance is hiring a

Web3 Data Scientist - LLM (Customer Service)

Binance is a leading global blockchain ecosystem behind the world’s largest cryptocurrency exchange by trading volume and registered users. We are trusted by over 250 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.

We are seeking a highly skilled professional to join our team, focusing on advancing customer service scheduling optimization through innovative AI solutions. This role involves researching and implementing cutting-edge algorithms to enhance scheduling systems, leveraging business domain knowledge to elevate the impact of AI products. The successful candidate will develop and refine Large Language Models (LLMs) to extract actionable insights, improve business decision-making, and optimize prompt design for more accurate outputs. Additionally, the role includes creating scalable and robust LLM/RAG frameworks tailored to customer service scheduling, fostering innovation and maintaining a competitive market edge.

Responsibilities:

• Responsible for the research and implementation of related algorithms in the fields of customer service scheduling optimization.
• In-depth understanding of customer service scheduling systems with the business domain knowledge to take the impact of AI product to the next level
• Develop and fine-tune Large Language Models (LLMs) to derive actionable insights and enhance business decision-making processes.
• Work as prompt engineers to refine and optimize prompt design, enabling more accurate and contextually relevant outputs from LLMs.
• Develop scalable and robust LLM/RAG frameworks that can be adapted to customer service scheduling, driving innovation and maintaining a competitive edge in the market.

Qualifications:

• Master's degree or higher in Computer Science, Data Science, Statistics, Mathematics, Computational Linguistics, or a related field.
• A minimum of 3 years of relevant industry experience in AI/ML. Hands-on experience in the field of machine learning, especially in large language models (LLMs) and generative artificial intelligence.
• Proficiency in programming languages such as Python, Java, with experience in machine learning (ML), natural language processing (NLP) libraries, and deep learning frameworks such as TensorFlow, PyTorch, Scikit-learn, SpaCy, and NLTK.
• Experience in the customer service field is required. Knowledge of the customer service scheduling process is necessary, and experience with related projects is preferred.