Ramp
Machine Learning Engineer
About this role
Lead fraud detection machine learning initiatives at Ramp, a high-growth fintech serving 70,000+ companies. You'll design and deploy ML models to combat fraud while maintaining frictionless user experiences, working closely with product and engineering teams on strategic roadmaps and production systems.
What you'll do
- Build and productionize machine learning models and rules-based systems to detect fraud, platform abuse, and identity theft
- Analyze large datasets using statistical and ML techniques to uncover fraud patterns and anomalies
- Partner with Fraud Engineering and Data Platform teams to integrate first and third-party data sources
- Design scalable data architectures and contribute to ML infrastructure improvements
- Set strategic roadmaps for fraud ML capabilities and lead technical decision-making
- Balance model accuracy with user experience to minimize false positives
What they're looking for
- Machine Learning (classification, anomaly detection, model evaluation)
- Python (numpy, pandas, scikit-learn, PyTorch)
- SQL (Snowflake, Postgres) and data querying
- Production ML deployment and backend systems integration
- Fraud detection and risk modeling fundamentals
- AI/agentic tools for development and analysis
- Startup environment adaptability and rapid iteration
- Statistical analysis and A/B testing
Benefits
- Flexible PTO and comprehensive health insurance (100% medical, dental, vision for employee)
- 401(k) with employer match, One Medical membership, and fertility HRA (up to $10,000/year)
- Parental leave up to 16 weeks at 100% pay with job protection
- Home office equipment, wellness stipend, and weekly coffee budget
- Relocation expense coverage to NYC or SF
- Pet insurance and in-office meals, snacks, and beverages
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Ramp
Ramp builds AI-first financial infrastructure and intelligence platforms that help businesses simplify complex finance operations, from spend management to FP&A and book-close workflows. The company is hiring Design Engineers, Software Engineers, fullstack AI Engineers, Onboarding Engineers, and Production Engineers to build scalable customer-facing experiences, developer APIs, fraud detection systems, and mission-critical infrastructure handling billions in transactions.
- Website
- ramp.com
Likely interview questions
- Describe a fraud detection model you've deployed to production—what were the key challenges in balancing precision and recall?
- How would you approach building a ML system that detects emerging fraud patterns while minimizing false positives for legitimate users?