Lead Machine Learning Engineer, TikTok Anti-Automation

The Business Risk Integrated Control (BRIC) team is missioned to:
- Protect TikTok users, including and beyond content consumers, creators, advertisers;
- Secure platform health and community experience authenticity;
- Build infrastructures, platforms and technologies, as well as to collaborate with many cross-functional teams and stakeholders.

The BRIC team works to minimize the damage of inauthentic behaviors on TikTok platforms (e.g. TikTok, CapCut, Resso, Lark), covering multiple classical and novel community and business risk areas such as account integrity, engagement authenticity, anti spam, API abuse, growth fraud, live streaming security and financial safety (ads or e-commerce), etc. In this team you'll have a unique opportunity to have first-hand exposure to the strategy of the company in key security initiatives, especially in building scalable and robust, intelligent and privacy-safe, secure and product-friendly systems and solutions. Our challenges are not some regular day-to-day technical puzzles -- You'll be part of a team that's developing novel solutions to first-seen challenges of a non-stop evolvement of a phenomenal product eco-system. The work needs to be fast, transferrable, while still down to the ground to making quick and solid differences.

Responsibilities:
- Build machine learning solutions to respond to and mitigate automated traffic to TikTok products/platforms. Such solutions include but are not limited to analyzing data collected by client-side security SDKs, anomalies in client environments and user behaviour.
- Improve modeling infrastructures, labels, features and algorithms towards robustness, automation and generalization, reduce modeling and operational load on risk adversaries and new product/risk ramping-ups.
- Uplevel risk machine learning excellence on privacy/compliance, interpretability, risk perception and analysis.