AI-driven workforce, forecasting and store execution software for retailers
Logile sells retail workforce and store-operations software covering labor planning, scheduling, forecasting and food safety. Its stack reads like an MLOps shop: MLflow, Weights & Biases, Airflow, Prefect and vector stores (FAISS, Pinecone, Weaviate) sit alongside a Java/Spring Boot core. Accelerating, engineering- and data-heavy hiring across India and the US targets the hard part, which is moving forecasting models from prototype into production.
Logile, Inc. is a privately held software company headquartered in Plano, Texas, founded in 2005, with 201–500 employees. It builds a connected platform for retailers that spans workforce management, employee scheduling, labor modeling, engineered labor standards, budgeting, task management, forecasting and food safety. The product helps store operators align staffing, shelves and daily execution. Teams operate in the United States and India, with engineering, data and support functions forming the core of current growth.
Logile runs Java with Spring Boot, React and Angular, PostgreSQL and MySQL, and Kafka. Its ML tooling includes Python, PyTorch, TensorFlow, scikit-learn, MLflow, Airflow and Kubernetes on AWS EKS, plus GCP and Azure.
Yes. Hiring is accelerating and centers on engineering and data roles, mostly at senior level, with support hiring as well. Openings are in India and the United States.
Logile is building demand forecasting and demand-response models, labor scheduling and pricing optimization, end-to-end ML pipelines, real-time inference systems and CI/CD for ML workflows.
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Logile, Inc.'s technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
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