Machine Learning Engineer Graduate (BRIC) - 2026 Start (PhD)

The Business Risk Integrated Control (BRIC) team is searching for talented interns to help us solve one of the internet's toughest challenges: protecting a global community from sophisticated, adversarial threats.
We are the engineering team responsible for the security and authenticity of TikTok, CapCut, and more. We stop spam, shut down fraud, prevent account takeovers, and ensure the interactions on our platform are genuine.
What you'll do:
- Tackle Real-World Adversarial Problems: You'll work on detecting fake engagement, API abuse, and financial fraud.
- Build Models at Massive Scale: Your work will involve analyzing billions of data points to find and stop bad actors.
- Push the Boundaries of AI: You'll have the chance to work with state-of-the-art techniques like Graph Neural Networks (GNNs), Transformers, and LLMs to model complex user behavior.

We are looking for talented individuals to join our team in 2026. As a graduate, you will get unparalleled opportunities for you to kickstart your career, pursue bold ideas and explore limitless growth opportunities. Co-create a future driven by your inspiration with TikTok.

Successful candidates must be able to commit to an onboarding date by end of year 2026. Please state your availability and graduation date clearly in your resume.

Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to TikTok and its affiliates' jobs globally. Applications will be reviewed on a rolling basis. We encourage you to apply as early as possible.

Responsibilities:
• Build machine learning solutions to respond to and mitigate business risks in TikTok products/platforms. Such risks include and are not limited to abusive accounts, fake engagements, spammy redirection, scraping, fraud, etc.
• 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.