Kakao Recommendation Team Internship Experience: 2-Month Project and Full-Time Crew Transition

charlie, a crew member of the Kakao Recommendation Team, shares their experience of transitioning to a full-time crew member through the Winter 2020 internship. The Recommendation Team has been independently running internships since 2018, aiming to apply machine learning-based recommendation technologies and improve user experience.

Project 1: Improving Service Metrics

The intern worked on a 2-week team project to improve the performance of similar item recommendations for cafe posts in the KakaoTalk Shop Tab. They analyzed the limitations of existing recommendation technologies, applied new approaches, and reflected these changes in the actual service. During the presentation, they realized the importance of experimental design through the sharp questions from team crew members.

Project 2: Scalable Random Walk CF Research

For a 6-week individual project, they conducted research on optimizing scalable random walk collaborative filtering (CF). They explored random walk methods to minimize performance degradation based on graph size, and went through the process of establishing data-based evidence with freedom in technology selection and resource support.

Value of the Internship and Transition

During the internship, they were able to set their career direction by experiencing Kakao's corporate culture, learning how machine learning is applied in real-world scenarios, and receiving mentoring from crew members. After the internship ended, they joined Part 1 of the Recommendation Technology team as a full-time member through the transition opportunity and are currently performing R&D duties.