Data/ML Engineer

1 day ago


New Delhi, India Gleantap Full time

About GleantapGleantap 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- 3–5+ years of experience in data engineering or applied ML. - Strong proficiency in Python, SQL, and one or more ML libraries (scikit-learn, LightGBM, XGBoost, PyTorch). - Experience with data pipelines (Airflow, dbt, or custom ETL). - Comfortable with event-driven systems (Kafka, Redis, ClickHouse or similar OLAP). - Understanding of ML lifecycle: training, serving, monitoring, retraining. - Ability to design time-based labels (avoiding data leakage). - Strong problem-solving skills and eagerness to work in a startup environment.Nice-to-Haves- MLOps tools (MLflow, BentoML, Ray Serve). - Experience with bandit algorithms, A/B testing, or uplift modeling. - Prior work with customer engagement, CRM, or subscription businesses.


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