Whatnot · 7 hours ago
Machine Learning Engineer, Fraud
New York, NY
Full-time
Hybrid
Mid, Senior Level
$245K/yr - $345K/yr
2+ years expWhatnot is the largest live shopping platform in North America and Europe, redefining e-commerce through community and entertainment. The Machine Learning Engineer, Fraud will design and deploy models to detect fraudulent behaviors, lead fraud detection architecture, and develop scalable data pipelines while collaborating with cross-functional teams.
CollectiblesE-CommerceInformation TechnologyMarketplaceTrading Platform
Responsibilities
Design, train, and deploy both traditional ML and LLM-powered 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
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 and continuously improve detection accuracy
Partner cross-functionally with Trust & Safety, Payments, and Infrastructure teams to develop features, labels, and model evaluation pipelines
Implement model monitoring and drift detection systems to ensure reliability and responsiveness
Contribute to fraud risk orchestration, combining rules, models, and heuristics for decision automation
Define and track key metrics and dashboards for fraud detection effectiveness (e.g., precision, recall, false-positive rate, latency)
Stay ahead of emerging fraud tactics and continuously translate insights into adaptive, production-ready systems
Qualification
Required
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
Ability to translate business risk into measurable ML solutions and collaborate across diverse teams
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
Company
Whatnot
Whatnot is a livestream shopping platform for buying and selling products.
501-1000 employees
H1B Sponsorship
Whatnot has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (34)
2024 (20)
2023 (18)
2022 (10)
Funding
Current Stage
Late StageTotal Funding
$974.7MKey Investors
CapitalGY Combinator Continuity FundAndreessen Horowitz
2025-10-28Series F· $225M
2025-01-08Series E· $265M
2022-07-21Series D· $260M
Leadership Team
Jeff Chang
Director of Engineering, Head of Growth
Recent News
2026-02-02
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Global Cosmetics News
2025-12-31
Company data provided by crunchbase