Senior Machine Learning Engineer, Access Safety - TikTok BRIC (Singapore)

The TikTok-BRIC-Access Safety team is missioned to protect the TikTok platform and users from malicious automation, fake traffic, and compromised devices.

We ensure all inbound traffic and device identities remain authentic and abuse-resistant.
In this team you'll have a unique opportunity to have first-hand exposure to the strategy of the company in key security initiatives.

You'll be part of a team that's developing novel solutions to first-seen challenges of a non-stop evolution of a phenomenal product eco-system:
- Perform access-risk detection and analysis using ML models and rule logic.
- Develop device authenticity labels.
- Execute real-time enforcement (block / throttle / challenge) and broader punishment mechanisms.
- Deliver signals, metrics, and dashboards to partner teams.

Responsibilities
- Perform access-risk detection and analysis using ML models and rule logic.
- Develop device authenticity labels.
- Execute real-time enforcement (block / throttle / challenge) and broader punishment mechanisms.
- Deliver signals, metrics, and dashboards to partner teams.



Minimum Qualifications
- Experience in safety, security, or risk control or related domains.
- Bachelor or above degree in computer science, statistics, or other relevant, machine-learning-heavy majors.
- Strong machine learning background.

Proficiency or publications in modern machine learning theories and applications such as deep neural nets, transfer/multi-task learning, reinforcement learning, time series or graph unsupervised learning.

Preferred Qualifications
- Experience in building detection and defense for Bot/large abusive traffic.
- Solid communication and collaboration skills with the ability to work effectively with internal teams in a cross-functional environment