Responsibilities:

• Design, develop, and maintain core components of Algo trading and Orders execution systems, ensuring high scalability, reliability, and performance.
• Collaborate closely with quantitative researchers, traders, and project managers to deliver innovative solutions that enhance trading and execution workflows.
• Implement robust algorithms to support a variety of trading strategies, such as market making and alpha capture.
• Lead or actively contribute to project management, ensuring timely delivery of high-quality solutions in a fast-paced environment.
• Leverage advanced machine learning and deep learning techniques to improve trading signals, risk management, and execution solutions.
• Explore and apply large language models (LLMs) and generative AI technologies (e.g., Qwen, Deepseek) to drive innovation in trading research and automation, including Retrieval-Augmented Generation (RAG) solutions.
• Stay abreast of the latest advancements in quantitative finance, AI, and machine learning, incorporating relevant research into practical applications.

Requirements:

• Bachelor, Master or PHD in CS,QuantFinance, Math, Physics or other releated disciplines. 2+ years+ experience in relevant work as a plus.
• Strong programming skills with experience in designing and building scalable trading or risk systems.
• Hands-on experience in quantitative trading and/or market analysis, with a deep understanding of market microstructure.
• Proven track record in delivering large-scale, production-level projects within complex environments or leading financial institutions.
• Practical experience with major machine learning and deep learning frameworks, including but not limited to,PyTorch,TensorFlow, Scikit-learn,XGBoost / LightGBM
• Experience with LLMs and related frameworks/packages, such as: Hugging Face Transformers, LangChain,Retrieval-Augmented Generation (RAG), Deepseek/Qwen API, Dify, or similar
• Ability to integrate and deploy deep learning and LLM models in production environments, including model serving, API integration, and monitoring.
• Excellent communication and teamwork skills, with the ability to work effectively in cross-functional teams.
• Strong interest and hands-on experience in applying LLMs and generative AI to solve real-world problems in finance, such as signal extraction, alpha research, knowledge management, or workflow automation.