TL;DR

Machine Learning Engineer (Collections): Developing and deploying production-ready ML models to optimize debt recovery and customer engagement with an accent on building scalable data pipelines and integrating models into workflows. Focus on translating business problems into data-driven solutions and implementing best practices for ML in production.

Location: Hybrid or full-time from our office in Mexico

Company

%hirify_global% is focused on optimizing financial solutions through innovative technology.

What you will do

Develop and deploy production-ready ML models for segmentation, outreach optimization, and risk prediction
Build and maintain data pipelines for model training, retraining, and monitoring
Collaborate with engineers to integrate models into automated workflows and decision systems
Define and implement best practices for ML in production
Translate business problems into data-driven solutions and communicate results clearly to stakeholders

Requirements

Experience: 2+ years in applied ML with strong focus on classic algorithms
Skills: Proficiency in Python and ML libraries such as Scikit-learn, XGBoost, LightGBM
Background: Strong engineering background with clean, maintainable code
Education: Degree from a recognized institution
Bonus: Experience with deep learning frameworks and cloud ML environments

Culture & Benefits

Relocation support to Mexico for employee and family
Flexible work arrangements
Healthcare coverage
Education and wellness budgets
20 days of annual leave and paid sick leave