Tech Stack

Description

As an MLOps Engineer at Cloudbeds, you will build and implement machine learning features that empower lodging customers to make data-driven pricing decisions, ensuring the reliability, scalability, and quality of our ML systems from development to production. You'll work cross-functionally to establish robust MLOps practices and own the end-to-end development of our revenue management application.

Requirements

• Expertise in Apache Airflow or similar orchestration tools (Prefect/Dagster)
• Experience building and deploying ML models in production
• Strong software engineering skills with focus on testing and reliability
• Ability to collaborate cross-functionally with product, engineering, and data science teams
• Experience with data pipeline design and large dataset processing

Responsibilities

• Develop and implement end-to-end ML features for revenue optimization
• Establish MLOps practices including CI/CD for model training, testing, deployment, and monitoring
• Design and maintain reliable data and ML pipelines using Apache Airflow
• Implement software quality testing for ML systems (unit, integration, end-to-end)
• Implement model performance monitoring (drift detection, data quality checks)