Senior ML Engineer - Financial Crime, Remote Equity

Lever, Inc.; Amsterdam; Hybrid; EUR 90,000 - 130,000; Full time

Benefits offered by this job

Stock options

Remote/hybrid across Europe

Personal & professional development

Employee wellbeing

Work & Swim Cyprus program

Job summary

Finom, a European fintech startup headquartered in Amsterdam, seeks a Senior Machine Learning Engineer to own end-to-end ML systems from development to production. You will deploy, monitor, and improve a Dynamic Risk Score used across all markets, with ML-driven detection for transaction processing and onboarding.

The role emphasizes scalable infrastructure, API services (FastAPI), and collaboration across a start-up environment. English fluency and a quantitative background are required.

Qualifications

• 5+ years of experience in ML engineering or data science with production deployments.
• Strong Python and SQL skills, plus cloud data platforms (Databricks).
• Experience with model monitoring and champion-challenger approaches.
• Ability to design scalable ML infrastructure and APIs (FastAPI).
• Proactive, autonomous in a startup setting; English fluency.

Responsibilities

• Full-stack ML model development (binary classification and regression) for fraud prevention during transaction processing and onboarding.
• Own and evolve the Dynamic Risk Score (DRS) across all markets with daily scoring.
• Handle a portfolio of transaction rules with ML-driven detection and alert optimization.
• Set up continuous monitoring of model and rule performance in production; develop champion-challenger framework.
• Participate in infrastructure development for ML model deployment and inter-service interactions.

Skills

SQL

Python

Model deployment

ML model monitoring

A/B evaluation

Education

Quantitative degree (math/engineering/economics/CS)

Tools

Databricks

FastAPI

Job description

Finom, a European fintech startup headquartered in Amsterdam, seeks a Senior Machine Learning Engineer to own end-to-end ML systems from development to production. You will deploy, monitor, and improve a Dynamic Risk Score used across all markets, with ML-driven detection for transaction processing and onboarding.

The role emphasizes scalable infrastructure, API services (FastAPI), and collaboration across a start-up environment. English fluency and a quantitative background are required.