Staff ML Engineer: Scalable Risk & Security Platforms

TikTok; San Jose (CA); On-site; USD 254,000 - 480,000; Full time

Job summary

TikTok in San Jose is seeking a Staff Machine Learning Engineer for the BRIC Community Health team. You will build scalable ML solutions to protect users and safeguard platform health, collaborating with cross‑functional partners across product, data, engineering, and risk.

This role requires a Master’s or higher in CS/Statistics/ML with 2+ years of ML experience, strong Python/Java/C++/Go, and experience with large‑scale data processing.

Qualifications

• Master's degree or higher in CS/Statistics/ML with at least 2 years of hands-on ML experience.
• Strong software engineering fundamentals with Python or Java/C++/Go; experience with Spark/Hadoop/Hive.
• Strong ML fundamentals with deep learning, graph learning, time-series, or transfer learning.
• Data-driven, results-oriented with strong problem-solving and analytical skills.
• Curiosity and ability to work autonomously in evolving risk environments.
• Excellent collaboration and communication across cross-functional teams.
• Preferred: industry experience in risk, fraud, abuse detection; experience with large-scale ML systems; hands-on with LLMs.

Responsibilities

• Build ML solutions to mitigate business risks in TikTok products.
• Improve modeling infrastructure, labels, features, and algorithms for robustness.
• Advance ML capabilities in risk perception, interpretability, privacy, and adversarial robustness.

Skills

Python

Java/C++/Go

Large-scale data processing

Deep learning

LLMs / Generative AI

Cross-functional collaboration

Problem solving

Education

Master's degree or above in CS/Statistics/ML

Tools

Spark

Hadoop

Hive

Python ML libraries

Job description

TikTok in San Jose is seeking a Staff Machine Learning Engineer for the BRIC Community Health team. You will build scalable ML solutions to protect users and safeguard platform health, collaborating with cross‑functional partners across product, data, engineering, and risk.

This role requires a Master’s or higher in CS/Statistics/ML with 2+ years of ML experience, strong Python/Java/C++/Go, and experience with large‑scale data processing.