Algorithm Engineer, Global Live - Business Intelligence - Singapore

About TikTok

TikTok is the leading destination for short-form mobile video. At TikTok, our mission is to inspire creativity and bring joy. TikTok's global headquarters are in Los Angeles and Singapore, and its offices include New York, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo.

Why Join Us

Creation is the core of TikTok's purpose. Our platform is built to help imaginations thrive. This is doubly true of the teams that make TikTok possible.

Together, we inspire creativity and bring joy - a mission we all believe in and aim towards achieving every day.

To us, every challenge, no matter how difficult, is an opportunity; to learn, to innovate, and to grow as one team. Status quo? Never. Courage? Always.

At TikTok, we create together and grow together. That's how we drive impact - for ourselves, our company, and the communities we serve.

Join us.

Diversity & Inclusion

Responsibilities

Team Introduction

The Live Platform Intelligence team's mission is to use model-driven and data-driven ways to promote core indicators on LIVE revenue and creator engagement, which includes: Build models for automated and intelligent operations to improve the efficiency and effectiveness of TT Live supply end, as well as discover and handle inappropriate user behavior and business anomaly, to assure the steady and persistent running of TT Live business. Spearheading analytical excellence with a penchant for creative problem-solving, our team functions at the intersection of data science and live content, ensuring an engaging and personalized experience for our global community of creators and viewers.

Responsibilities

1. Participate in the optimization of ByteDance LIVE business and serve the LIVE experience of billions of global users.

2. Adopt cutting-edge machine learning models to improve business metrics (LIVE revenue and LIVE content quality), and bring creators/operators the ultimate experience in LIVE business.

3. Deeply participate in product/business discussions, analyze and understand user behaviour patterns, and provide optimization directions for improvement.

Qualifications

Minimum Qualifications

- Master's degree or above in Computer Science, or equivalent practical experience

- Familiar with commonly used machine learning and deep learning algorithms, including but not limited to DNN, NLP, CV, etc.

- Familiar with at least one of Flink, Spark, Hive etc., with big data parallel processing experience

- Excellent problem-solving and critical thinking skills, and solid maths foundation, including probability statistics, numerical optimization, etc.

Preferred Qualifications

- Experience in large-scale recommend/advertising systems, risk control systems or LLM is preferred