Senior ML Engineer: E‑Commerce Risk & Fraud Defense

TikTok USDS Joint Venture; San Jose (CA); On-site; USD 187,000 - 360,000; Full time

Job summary

TikTok USDS Joint Venture LLC is seeking a skilled Machine Learning Engineer to join the E‑Commerce Risk Control team in San Jose. You will design, implement, and deploy ML models to detect fraud, abuse, and security risks across TikTok’s e‑commerce platforms, collaborating with data scientists, engineers, and product teams.

You'll work with representation learning, graph models, and deep learning, building scalable solutions that protect users and merchants while maintaining privacy.

Qualifications

• Master’s degree in CS, math, ML or related STEM field.
• 3+ years building ML models for large-scale internet projects.
• Proficiency in C++, Java, Python with ML platform familiarity.
• Strong grounding in supervised/unsupervised/deep learning techniques.
• Ability to work autonomously with data-driven mindset.

Responsibilities

• Invent, implement, and deploy ML algorithms to mitigate e-commerce risks.
• Leverage representation learning, graphs, deep learning to improve detection.
• Monitor metrics, detect risk trends, refine risk strategies and governance.
• Mine large e-commerce data to improve model precision and robustness.
• Advance privacy-aware risk ML capabilities and scalable systems.

Skills

Critical thinking

Autonomy

Data-driven decision making

Education

Master’s degree in Computer Science / Mathematics / Machine Learning

PhD in Computer Science / ML / Statistics (preferred)

Tools

C++

Java

Python

ML platforms (TensorFlow/PyTorch)

Job description

TikTok USDS Joint Venture LLC is seeking a skilled Machine Learning Engineer to join the E‑Commerce Risk Control team in San Jose. You will design, implement, and deploy ML models to detect fraud, abuse, and security risks across TikTok’s e‑commerce platforms, collaborating with data scientists, engineers, and product teams.

You'll work with representation learning, graph models, and deep learning, building scalable solutions that protect users and merchants while maintaining privacy.