Zepz

1 Job

624 Employees

About the Company

Zepz is powering two leading global payments brands: WorldRemit and Sendwave. We represent brands that disrupted an industry previously dominated by offline legacy players by taking international money transfers online - making global digital payments fairer, faster, and more flexible. Our brands currently send from 50 to 130 countries, operate in more than 5,000 money transfer corridors worldwide and employ over 1,400 people globally. Zepz is a remote-first employer, with team members located across six continents.

On the sending side our brands are 100% digital (cashless), increasing convenience and enhancing security. For those receiving money, our brands offer a wide range of options including bank deposit, cash collection, mobile airtime top-up and mobile money.

www.zepzpay.com

Listed Jobs

Company Name: Zepz
Job Title: Senior Machine Learning Engineer
Job Description: Job Title: Senior Machine Learning Engineer Role Summary: Own the full lifecycle of fraud detection machine learning models for a FinCrime team, translating business fraud patterns into scalable, production-ready solutions with robust monitoring and CI/CD. Expectations: Deliver end-to-end models that provide measurable value in production; maintain high ownership and continuous improvement; collaborate closely with backend engineering and data science; ensure models are well-tested, documented, and drift-monitored. Key Responsibilities: - Design, develop, and deploy fraud detection models (Gradient Boosting, XGBoost/LightGBM). - Perform feature engineering, hypothesis generation, and data extraction using SQL and dbt. - Build and maintain infrastructure (Docker, orchestration, cloud deployment) for real-time inference. - Implement automated CI/CD pipelines and model monitoring for performance decay and drift. - Serve as technical liaison between backend engineers and data science to integrate ML into core products. - Conduct high-impact experiments on new data sources and modeling techniques. Required Skills: - 6+ years of professional ML development and production experience. - Proficiency in Python, unit testing, clean architecture, and production-grade code. - Expertise in Gradient Boosting (XGBoost/LightGBM), feature engineering, and translating fraud patterns into ML problems. - Advanced SQL and dbt for feature store management. - Experience with Docker, orchestration (Kubernetes/others), and cloud ML deployment. - Familiarity with Scikit‑Learn, BigQuery/Redshift/Databricks, and model monitoring frameworks. - Strong problem‑solving, ownership, and communication skills. Required Education & Certifications: - Bachelor’s or Master’s degree in Computer Science, Engineering, Statistics, or related field. - Certifications in cloud ML platforms (e.g., AWS SageMaker, GCP Vertex AI) or ML engineering are advantageous.