Ecommerce Risk ML Engineer - Protect & Optimize Trust

TikTok Inc.; Seattle (WA); On-site; USD 154,000 - 301,000; Full time

Job summary

TikTok Inc. is seeking a lead E-Commerce Risk Control scientist to build ML models and risk systems for the TikTok Shop ecosystem. You will collaborate across product, engineering, and business teams to design, implement, and deploy scalable risk detection solutions that protect buyers, sellers, and creators.

The role emphasizes quantitative modeling, data-driven decision making, and strong communication to stakeholders while advancing fraud prevention in fast-growing e-commerce settings.

Qualifications

• Master's degree in CS, Math, ML or related STEM field; programming with Java, C++, Python.
• 3+ years building and delivering ML models for large-scale projects.
• Experience with forecasting, ML and statistical tools; clear communication of results.
• Ability to think creatively and solve problems.

Responsibilities

• Invent, implement, and deploy ML algorithms to mitigate risks in TikTok products/platforms.
• Build prototypes; conduct experiments; communicate insights to Product and Tech teams.
• Collaborate with cross-functional teams to enhance automation processes.
• Develop data querying infrastructure for offline/online analysis; identify risk weaknesses.
• Define risk control measurements; quantify and monitor risk-related metrics.
• Maintain technical documents and communicate results to diverse audiences.

Skills

Java

C++

Python

Scala

R

Ruby

Matlab

Education

Master's degree in CS/Math/ML

PhD in CS/ML/Statistics/OR

Job description

TikTok Inc. is seeking a lead E-Commerce Risk Control scientist to build ML models and risk systems for the TikTok Shop ecosystem. You will collaborate across product, engineering, and business teams to design, implement, and deploy scalable risk detection solutions that protect buyers, sellers, and creators.

The role emphasizes quantitative modeling, data-driven decision making, and strong communication to stakeholders while advancing fraud prevention in fast-growing e-commerce settings.