F2OnSite
Our client is a fast-growing, Series C fintech company focused on empowering the next generation with financial tools and education. With over 5.5 million users and $175M+ raised, they're transforming how Gen Z banks and builds financial literacy.
Remote - Senior Machine Learning Engineer - Risk and Fraud - SME
This is a Direct Hire Position
Job Summary:
We're seeking a
Senior Machine Learning Engineer
with deep experience in
Risk & Fraud
detection systems. In this role, you'll lead the design, development, and deployment of ML models that help detect and prevent fraudulent activity in real-time.
Responsibilities:
Build and deploy ML models to detect and mitigate fraud risk Own the technical roadmap for ML initiatives in Risk/Fraud Partner with Ops teams to respond to real-time fraud scenarios Use SQL to extract, transform, and analyze large datasets Write scalable, production-ready Python code for ML systems Design A/B tests and statistically sound experiments Work cross-functionally with Engineering, Product, and Risk teams Required Qualifications:
5+ years of experience in Data Science or ML Engineering Strong Python and SQL skills Proven experience deploying ML models in production Experience designing fraud detection systems or risk models Strong communication skills (technical + non-technical audiences) Preferred (Not Required):
Experience in fintech, banking, or financial services Familiarity with real-time fraud mitigation or credit/lending systems Perks & Benefits:
Competitive base salary + equity Fully remote (U.S. only) Health, dental, and vision insurance Unlimited PTO & flexible schedule 401(k) with company match Paid parental leave
Job Summary:
We're seeking a
Senior Machine Learning Engineer
with deep experience in
Risk & Fraud
detection systems. In this role, you'll lead the design, development, and deployment of ML models that help detect and prevent fraudulent activity in real-time.
Responsibilities:
Build and deploy ML models to detect and mitigate fraud risk Own the technical roadmap for ML initiatives in Risk/Fraud Partner with Ops teams to respond to real-time fraud scenarios Use SQL to extract, transform, and analyze large datasets Write scalable, production-ready Python code for ML systems Design A/B tests and statistically sound experiments Work cross-functionally with Engineering, Product, and Risk teams Required Qualifications:
5+ years of experience in Data Science or ML Engineering Strong Python and SQL skills Proven experience deploying ML models in production Experience designing fraud detection systems or risk models Strong communication skills (technical + non-technical audiences) Preferred (Not Required):
Experience in fintech, banking, or financial services Familiarity with real-time fraud mitigation or credit/lending systems Perks & Benefits:
Competitive base salary + equity Fully remote (U.S. only) Health, dental, and vision insurance Unlimited PTO & flexible schedule 401(k) with company match Paid parental leave