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Mid LevelFull-timePythonRustMachine LearningPyTorchML
Salary Range
$102,000 - $138,000 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
We are looking for a Fraud Detection Machine Learning Engineer to join Whatnot, the largest live shopping platform in North America and Europe. This role involves designing, training, and deploying ML models to detect fraudulent behaviors across users, payments, and marketplace interactions.
Key Responsibilities
- →Design, train, and deploy both traditional ML and LLM-powered models to detect fraudulent behaviors
- →Lead the end-to-end architecture of fraud detection, prevention, and intervention systems
- →Build intelligent user graphs to model behavioral patterns, collusion networks, and account connectivity
- →Develop scalable data pipelines and real-time inference systems supporting high-volume, low-latency ML workloads
- →Conduct deep behavioral and adversarial data analysis to uncover fraud trends
- →Partner cross-functionally with Trust & Safety, Payments, and Infrastructure teams
- →Implement model monitoring and drift detection systems
- →Contribute to fraud risk orchestration, combining rules, models, and heuristics
- →Define and track key metrics and dashboards for fraud detection effectiveness
Requirements
- ✓Bachelor’s degree in Computer Science, a related field, or equivalent work experience
- ✓2–6 years of experience in machine learning or software engineering
- ✓Strong proficiency in Python and ML libraries
- ✓Solid backend development skills and experience deploying ML models to production
- ✓Experience in data analysis and ETL for data pipeline building
- ✓Familiarity with fraud detection techniques
- ✓Experience with data orchestration frameworks and feature store design
- ✓Ability to translate business risk into measurable ML solutions
