Data / ML Engineer

About Gleantap

Gleantap is a customer engagement platform powering fitness, wellness, and service businesses. We're evolving into an AI-native platform, where intelligent agents predict churn, upsell opportunities, and automate member engagement.

We're looking for a Data / ML Engineer who can bridge the gap between data engineering and applied machine learning, building pipelines, training models, and deploying them into production at scale.

Responsibilities

• Design and build data pipelines to transform raw events (visits, purchases, campaigns) into usable features.
• Define and compute labels (e.g., churn, upsell, lead quality) from historical events.
• Develop and train ML models (e.g., churn prediction, upsell propensity, lead scoring) using Python (scikit-learn, LightGBM, XGBoost).
• Build real-time inference services to serve predictions into production systems.
• Set up retraining and monitoring pipelines (Airflow, MLflow, or similar).
• Collaborate with backend engineers to integrate model outputs into Gleantap workflows.
• Ensure data quality, reproducibility, and compliance (HIPAA for healthcare customers).

Requirements

Nice-to-Haves