- Could you introduce yourself and tell us about you? Your current / recent jobs and employers? Previous companies and jobs?
He has over 8 years of experience in the industry, mainly focusing on investment and banking-related work. He has both in-house and vendor experience in AI and machine learning, particularly supporting quantitative investment projects. He has also worked on trading-related tasks in Web3, Hong Kong stocks, and other technical areas, including projects that support patent creation using machine learning. Currently, he is working at XXXX, where he handles AI solutions for portfolio recommendations, user engagement, and investment products designed for users with limited investment knowledge. He has also been involved in building AI agents and other machine learning initiatives. - What skill(s) / experience would you self-describe as strongest or specialist in?
He has hands-on experience with deeper AI development, including neural network design and loss-function-level tasks. He has previously led teams, but his current role is more focused on individual contribution due to the company culture. Still, he manages and supports multiple projects and collaborates closely with team members. He mainly works under the CDC brand and often handles several projects at the same time—recently managing around 10 projects simultaneously—which highlights his multitasking and project management skills.
- Do you have the lists of key criteria’s according to the clients’ requirements?
He works with different programming languages depending on the task, mainly using Python but also working with Scala and occasionally TypeScript based on project requirements. His focus is on AI and machine learning, including deep learning and large models, and he works closely with these technologies in both his main role and side projects. One of his recent projects involved building an automated Texas Hold’em AI using the latest techniques, complete with live streaming and low-latency responses. He has experience handling many types of data—investment data, social media data, sound waves, and aircraft text logs. Before shifting focus, he worked heavily in the investment field and supported projects related to traffic and aircraft analysis. He now deals with extremely large datasets, especially from crypto exchanges that generate massive volumes of data every second.
