Data Scientist - LLM (Customer Service)

Binance is a prominent global blockchain ecosystem that operates the world's largest cryptocurrency exchange based on trading volume and user registrations. Our platform is relied upon by more than 250 million individuals across 100+ countries, known for our top-notch security, transparent user fund management, high-speed trading engine, extensive liquidity, and diverse range of digital asset offerings. Binance caters to various services including trading, finance, education, research, payments, institutional solutions, Web3 features, and more. Our mission is to utilize the potential of digital assets and blockchain technology to establish an accessible financial ecosystem that promotes financial freedom and enhances financial inclusivity globally.

We are in search of a talented professional to contribute to our team by driving innovation in customer service scheduling optimization through the application of cutting-edge AI solutions. This position involves conducting research and implementing advanced algorithms to improve scheduling systems, utilizing specialized business knowledge to maximize the effectiveness of AI products. The ideal candidate will focus on developing and optimizing Large Language Models (LLMs) to extract valuable insights, enhance decision-making processes, and refine prompt designs to provide more accurate outcomes. Additionally, this role will involve designing adaptable and resilient LLM/RAG frameworks tailored to optimize customer service scheduling, promoting innovation and ensuring a competitive advantage in the market.

Responsibilities:

• Conduct research and implement relevant algorithms in the realm of customer service scheduling optimization.
• Utilize strong comprehension of customer service scheduling systems and leverage business domain expertise to amplify the impact of AI products.
• Develop and fine-tune Large Language Models (LLMs) to generate actionable insights and elevate business decision-making capabilities.
• Collaborate as prompt engineers to enhance prompt design accuracy, enabling LLMs to deliver contextual and precise outputs.
• Create scalable and sturdy LLM/RAG frameworks that can be customized for customer service scheduling, encouraging innovation and maintaining a competitive edge.

Qualifications:

• Hold a Master's degree or higher in Computer Science, Data Science, Statistics, Mathematics, Computational Linguistics, or a related field.
• Possess a minimum of 3 years of relevant industry experience in AI/ML with practical involvement in machine learning, particularly in large language models (LLMs), and generative artificial intelligence.
• Proficient in programming languages like Python, Java, with practical experience in machine learning (ML), natural language processing (NLP) libraries, and deep learning frameworks including TensorFlow, PyTorch, Scikit-learn, SpaCy, and NLTK.
• Demonstrate prior experience in the customer service sector, essential knowledge of customer service scheduling processes, and a preferred background in related projects.