資本額9500萬員工人數350人
【AI Team】
At CMoney, our mission is to assist people in their lifelong investment. To this end, we have already launched several services and apps to help users make decisions on different matters. CMoney has one XLab and three business units: finance, consumer, and community. In our finance BU, we have the most popular stock mobile app and stock forum in Taiwan. Meanwhile, we collaborate with 50+ investment KOLs to help users succeed in investment. Our invoice app in our consumer BU has almost 1.8 million monthly active users. All of our products have had more than 4.1 million monthly active users. Currently, CMoney is at the fast-growing stage, and thus we are looking for brilliant talents to join our team, especially the ones with integrity, high social interest and a growing mindset. For more detail of CMoney, please refer to the following link: https://cmy.tw/00BWhP .
Our AI team focuses on utilizing large language models to do text classification and automatic summarization to enhance our products and to provide values to our users. Our AI team is also responsible for developing and establishing cross-product recommendation systems so that our products can offer personalized features for the users. Moreover, our AI team employs generative AI techniques or services to originate brand new products like an AI-powered social network and productivity tools. If you not only love to keep track of the latest trend of AI development and techniques but also are passionate about implementing the relevant algorithms by yourself, we welcome you to join us.
【As such, you will】
1. Design, develop, train, and integrate AI models to our services or products.
2. Analyze and diagnose the problems and bottlenecks of current AI models.
3. Collaborate with other product and data teams to propose and provide better
solutions.
4. Make CMoney service more intelligent, and make CMoney data more beneficial to
the community.
5. Last but not least make our customer success.
【Must have】
1. BS/MS/Ph.D in EE, CS, IM, Statistics, and Applied Math or related field.
2. Familiar with at least one of the following machine learning frameworks: Weka,
Scikit learn, Spark, PyTorch, and Tensorflow.
3. Ability to collect the data, train models, fine-tune models, and deploy models.
4. Broad knowledge of deep learning, machine learning, statistics, and optimization.
5. Experience in training on large-scale (TB) datasets and training on distributed environment is a plus