Machine Learning Engineer (Ecomm Algo RCS - Account Security / ATO focused) - USDS

San Jose, California, United States

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About the Team
The E-Commerce Risk Control & Security (RCS) team works to protect our users, including and beyond buyer, seller, creator; to minimize the damage of inauthentic behaviors on TikTok Shop (TTS) E-Commerce platforms, covering multiple classical and novel business risk areas such as account integrity, incentive abuse, malicious behaviors, brushing, click-farm, information leakage, etc. By utilizing Machine Learning models, LLMs, graphs, & algorithm, RCS dynamically controls risk scenarios, identify Modus Operandi (MO), and enforces rules in realtime to protect TTS and minimize capital loss from fraudsters, hackers, and questionable buyers, sellers, and creators. Through building software systems, risk models and operational processes, as well as collaborating with many cross-functional teams and stakeholders, RCS team operates the safest and most trusted place worldwide to transact online by securing the integrity of the e-commerce ecosystem and providing a safe shopping experience on the TTS platform.

Responsibilities:
- Building software systems, risk models and operational processes, as well as collaborating with many cross-functional teams and stakeholders, to identify cybersecurity threats, prevent accounts takenover, and the corresponding mitigation strategies in various scenarios
- Invent, implement, and deploy state of the art machine learning algorithms, to respond to and mitigate business risks in TTS products/platforms.
- Build prototypes and explore conceptually new solutions, define and conduct experiments to validate/reject hypotheses, and communicate insights and recommendations to Product and Tech teams
- Collaborate with cross-functional teams from multidisciplinary science, engineering and business backgrounds to enhance current automation processes
- Develop efficient data querying infrastructure for both offline and online analysis, uncover evolving attack motion, identify weaknesses and opportunities in risk defense solutions, explore new space from the discoveries.
- Define risk control measurements. Quantify, generalize and monitor risk related business and operational metrics. Align risk teams and their stakeholders on risk control numeric goals, promote impact-oriented, data-driven data science practices for risks.
- Maintain technical documents and communicate results to diverse audiences with effective writing, visualizations, and presentations

In order to enhance collaboration and cross-functional partnerships, among other things, at this time, our organization follows a hybrid work schedule that requires employees to work in the office 3 days a week, or as directed by their manager/department. We regularly review our hybrid work model, and the specific requirements may change at any time.
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Tags: E-commerce Engineering LLMs Machine Learning ML models Security

Region: North America
Country: United States

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