Senior Machine Learning Engineer (Fintech)

TL;DR

Senior Machine Learning Engineer (Fintech): Building and deploying predictive models and decision systems for fraud detection, risk monitoring, and customer lifetime value with an accent on quantitative rigor and production-ready ML. Focus on framing ambiguous business problems into optimization tasks, running causal analyses, and implementing robust MLOps pipelines.

Location: Brazil | Rio de Janeiro

Company

A payment and software service provider serving small, local businesses across Europe.

What you will do

• Design and deploy predictive models for fraud, risk monitoring, onboarding, and pricing.
• Frame ambiguous business problems as modeling, inference, or optimization tasks.
• Conduct A/B testing, uplift modeling, and causal analyses to measure business impact.
• Build data pipelines for training and serving with a focus on data quality and reproducibility.
• Productionize models with monitoring, drift detection, and automated retraining.
• Collaborate with product managers and engineers to integrate models into operational workflows.

Requirements

• Strong foundations in statistics and machine learning.
• Proficiency in Python (pandas, scikit-learn, NumPy) and SQL.
• Hands-on experience deploying ML models in production.
• Solid command of supervised and unsupervised learning (gradient boosting, clustering, etc.).
• Experience with cloud platforms, CI/CD, APIs, and infrastructure as code.
• Strong software engineering fundamentals including testing and maintainability.

Nice to have

• Experience in regulated industries such as payments, fintech, banking, or fraud prevention.
• Expertise in churn modeling, forecasting, or recommendation systems.
• Background in operations research, mathematical programming, or stochastic optimization.
• Knowledge of MLOps, feature stores, and model governance.
• Experience with PyTorch or TensorFlow.

Culture & Benefits

• High-energy and connected culture focused on supporting small businesses.
• Continuous learning opportunities and a supportive professional community.
• Comprehensive benefits package.
• Inclusive environment and equal opportunity employer.