
Artificial Intelligence Model Specialist
2 weeks ago
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.
Our team of experts bridges the gap between data engineering and applied machine learning, building pipelines, training models, and deploying them into production at scale.
Responsibilities:- Design and build scalable data pipelines to transform raw events into usable features.
- Develop and train ML models 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).
- Collaborate with backend engineers to integrate model outputs into workflows.
- Ensure data quality, reproducibility, and compliance with industry regulations.
- 3–5+ years of experience in data engineering or applied ML.
- Strong proficiency in Python, SQL, and one or more ML libraries.
- Experience with data pipelines (Airflow, dbt, or custom ETL).
- Comfortable with event-driven systems (Kafka, Redis, ClickHouse).
- Understanding of ML lifecycle: training, serving, monitoring, retraining.
- Ability to design time-based labels and ensure data integrity.
- Strong problem-solving skills and eagerness to work in a fast-paced startup environment.
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