Fresh Grad Hire - Machine Learning Engineer (Large Model Applications)

Futu's AI Team is dedicated to integrating artificial intelligence technology into financial services, building more efficient and intelligent products and services.

The team covers core areas including quantitative research, intelligent investment advisory, search and recommendation systems, Q&A, content generation, and AI platform development.

We look forward to passionate and innovative individuals joining us in exploring the future blueprint of AI in finance.

Key Responsibilities

1. Research cutting-edge technologies in areas such as machine learning and natural language processing, including but not limited to large language models (LLMs), multimodal models, world models, generation, dialogue, and information extraction.
2. Apply LLMs to core enterprise scenarios to enhance model performance through methods such as Continued Pretraining, Supervised Fine-Tuning (SFT), Reinforcement Learning (RL), and Retrieval-Augmented Generation (RAG).
3. Explore the application of the most advanced AI technologies, stay abreast of academic and industry trends, contribute to open-source projects or publish research papers, and enhance the team's influence in the field of large models.

Requirements

1. Master's or Ph.D. Candidate majoring in Computer Science, Mathematics, or a related field.
2. Solid foundation in machine learning, NLP, and LLMs. Strong conceptual and hands-on abilities, excellent research skills. Prior experience in publishing at top-tier conferences (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR) or awards in mathematics/programming competitions is a plus.
3. Passionate about the practical application of AI technology and groundbreaking innovations, committed to combining technological advancement with real-world value.
4. Strong self-motivation, agile thinking, pursuit of first principles, courage to tackle unknown challenges, enthusiasm for exploring the technological frontier, and the ability to proactively learn and grow rapidly.
5. Open to candidates graduating between January 2025 and August 2026.

*Only shortlisted candidates will be contacted.