Are you passionate about harnessing the power of machine learning to drive business growth? As a Machine Learning Operations (MLOps) Engineer, you will play a vital role in building and deploying scalable machine learning infrastructure on Databricks. Our team is dedicated to creating award-winning software for top-tier clients across various industries. As an MLOps Engineer at AgileEngine, your primary responsibilities will include: - Building and maintaining scalable ML infrastructure on Databricks, leveraging Unity Catalog and feature stores to support model development and deployment; - Designing and implementing frameworks for detecting data and model drift, ensuring continuous monitoring and high reliability of ML models in production; - Developing model calibration frameworks and establishing versioning practices to maintain transparency and reproducibility across the ML lifecycle; - Designing and optimizing reinforcement learning (RL) orchestration pipelines, including Contextual Bandits, for real-time execution in low-latency environments; - Creating automated frameworks for training, retraining, and validating ML models, enabling efficient experimentation and deployment; - Implementing CI/CD best practices to streamline the deployment and monitoring of ML models, integrating with Databricks workflows and Git-based version control systems; - Collaborating closely with ML Scientists to ship, deploy, and maintain models; - Building tools for model performance monitoring, operational analytics, and drift mitigation, ensuring reliable operation in production environments. To succeed in this role, you should possess: - A strong background in MLOps, ML Engineering, Data Engineering, or related fields, with experience deploying and managing ML workflows in production environments; - Proficiency in using Python, Databricks, Apache Spark, ML Flow, Unity Catalog, and feature stores; - Familiarity with ML lifecycle tools such as MLflow, Kubeflow, and Airflow; - Strong knowledge of Git workflows, CI/CD practices, and tools like GitLab or similar; - Upper-Intermediate English level. In return for your expertise, you can expect: - Accelerated professional growth through mentorship, TechTalks, and personalized growth roadmaps; - Competitive USD-based compensation and budgets for education, fitness, and team activities; - A selection of exciting projects with modern solutions development and top-tier clients that include Fortune 500 enterprises and leading product brands; - Flextime to tailor your schedule for an optimal work-life balance, with options for working from home and going to the office. "The ideal candidate will have a strong passion for machine learning and operations, excellent problem-solving skills, and the ability to collaborate effectively with cross-functional teams." We look forward to hearing from you!