Why Join Us
Creation is the core of TikTok's purpose. Our products are built to help imaginations thrive. This is doubly true of the teams that make our innovations possible. Together, we inspire creativity and enrich life - a mission we aim towards achieving every day. To us, every challenge, no matter how ambiguous, 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 users we serve. Join us.
The Business Risk Integrated Control (BRIC) team is missioned to:
- Protect ByteDance 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 ByteDance platforms (e.g. TikTok, CapCut,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
- Develop machine learning solutions to proactively address and mitigate business risks across ByteDance products and platforms. These risks include, but are not limited to, abusive accounts, fake engagements, spam redirection, scraping, fraud, and others.
- Enhance modeling infrastructure, labeling processes, feature engineering, and algorithms to improve robustness, automation, and generalization, while reducing both modeling and operational burden on risk management teams and easing the integration of new products and risk areas.
- Drive improvements in risk-related machine learning practices, focusing on privacy and compliance, interpretability, and advanced risk perception and analysis.
Report job
