AI Algorithm Engineer

1 week ago


Hong Kong Island, Hong Kong SAR China AQUMON Full time

Job Description As an AI Algorithm Engineer at AQUMON, you will play a crucial role in processing and analyzing financial market news, product documentation, and research materials from central banks using large language models. Your expertise will help distill and refine information from complex texts to enhance portfolio performance and risk management strategies. This role involves deep engagement with AI technologies to extract actionable insights from vast amounts of financial data, contributing significantly to our innovative portfolio solutions. Location: Shenzhen/Hong Kong. Employment type: Full-time. Key Responsibilities Develop and implement algorithms using large language models to analyze financial documents and news. Extract and interpret key data points from financial texts to aid in decision-making processes. Collaborate with a team of engineers and researchers to enhance existing models and develop new methodologies for data analysis. Stay updated with the latest advancements in AI and machine learning technologies, applying them to solve complex problems in wealth management. What We Are Looking For Qualifications: PhD in Machine Learning, Deep Learning, or related fields with exceptional engineering skills. Passion: Strong enthusiasm for the application of model-driven and AI technologies in the wealth management sector. Culture Fit: Ability to adapt to a startup culture, thrive in a fast-paced and dynamic environment, and commitment to hard work and innovation. Language Proficiency: Fluency in both English and Mandarin to effectively communicate with a diverse client base. Why Join AQUMON? Join a FinTech leader that is deeply invested in using sophisticated mathematical models and AI to revolutionize wealth management. Be part of a renowned team supported by a foundation of excellence, making significant contributions to the industry. Work in an environment that values innovation, excellence, and individual contributions. Published on #J-18808-Ljbffr


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