Senior Machine Learning Engineer, TikTok BRIC Access Safety

Description

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.

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.

Requirements

Minimum Qualifications
- Solid engineering skills. Proficiency in Python, SQL, Hive, Spark, Linux.
- 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.
- Ability to think critically, objectively, rationally. Reason and communicate in a result-oriented, data-driven manner.

Preferred Qualifications
- Bachelors or above degree in computer science, statistics, or other relevant, machine-learning-heavy majors.
- 3 years of industry experience in a software development environment.
- Experience in building detection and defense for Bot/large abusive traffic.