Machine Learning Engineer, Fraud

Join Whatnot as a Machine Learning Engineer to design, train, and deploy ML models to detect fraudulent behaviors across users, payments, and marketplace interactions. Lead the end-to-end architecture of fraud detection, prevention, and intervention systems, balancing platform security with a seamless user experience.

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, ideally in risk, fraud, or trust & safety domains
• Strong proficiency in Python and ML libraries (e.g., scikit-learn, PyTorch, LightGBM)
• Solid backend development skills and experience deploying ML models to production (batch or real-time)
• Experience in data analysis and ETL (SQL, Spark, DBT) for data pipeline building
• Familiarity with fraud detection techniques such as chargeback prediction, anomaly detection, or graph-based modeling
• Experience with data orchestration frameworks (Dagster, Kubeflow) and feature store design

Benefits

• Generous Holiday and Time off Policy
• Health Insurance options including Medical, Dental, Vision
• Work From Home Support
• Home office setup allowance
• Monthly allowance for cell phone and internet
• Care benefits
• Monthly allowance for wellness
• Annual allowance towards Childcare
• Lifetime benefit for family planning, such as adoption or fertility expenses
• Retirement; 401k offering for Traditional and Roth accounts in the US (employer match up to 4% of base salary) and Pension plans internationally
• Monthly allowance to dogfood the app
• Parental Leave
• 16 weeks of paid parental leave + one month gradual return to work