Machine Learning Engineer, Risk Data Mining - USDS
$129.96k - $246.24kTik Tok
Machine Learning Engineer, Risk Data Mining - USDS Machine Learning Engineer, Risk Data Mining - USDS Get AI-powered advice on this job and more exclusive features. Responsibilities The USDS-Platform and Community Integrity (PaCI) team is missioned to:
- Protect U.S. TikTok users, including and beyond content consumers, creators, advertisers;
- Secure platform health and community experience authenticity;
- Build infrastructures, platforms and technologies, as well as to collaborate with many cross-functional teams and stakeholders.
- Build machine learning solutions to respond to and mitigate business risks in TikTok products/platforms. Such risks include and are not limited to abusive accounts, fake engagements, spammy redirection, scraping, fraud, etc.
- 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.
- Master or above degree in computer science, statistics, or other relevant, machine-learning-heavy majors.
- Solid engineering skills. Proficiency in at least two of: Linux, Hadoop, Hive, Spark, Storm.
- 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 result-oriented, data-driven manner. High autonomy.
- Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;
- Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and
- Exercising sound judgment.
Vacancy posted 2 days ago
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