As a Machine Learning Operations Engineer, you will be responsible for building and maintaining scalable machine learning infrastructure on Databricks. This includes leveraging Unity Catalog and feature stores to support model development and deployment. You will also design and implement frameworks for detecting data and model drift, ensuring continuous monitoring and high reliability of ML models in production. Additionally, you will develop model calibration frameworks and establish versioning practices to maintain transparency and reproducibility across the ML lifecycle. Another key aspect of this role is designing and optimizing reinforcement learning (RL) orchestration pipelines, including Contextual Bandits, for real-time execution in low-latency environments. You will create automated frameworks for training, retraining, and validating ML models, enabling efficient experimentation and deployment. Furthermore, you will implement CI/CD best practices to streamline the deployment and monitoring of ML models, integrating with Databricks workflows and Git-based version control systems. You will work closely with ML Scientists to ship, deploy, and maintain models. Finally, you will build tools for model performance monitoring, operational analytics, and drift mitigation, ensuring reliable operation in production environments. MUST HAVES 1. At least 3 years of experience in MLOps, ML Engineering, Data Engineering or related roles, focusing on deploying and managing ML workflows in production environments; 2. 5+ years of experience using Python; 3. Proficient in using Databricks (2-3 years), Apache Spark, ML Flow, Unity Catalog, and feature stores; 4. Familiarity with ML lifecycle tools such as MLflow, Kubeflow, and Airflow; 5. Strong knowledge of Git workflows, CI/CD practices, and tools like GitLab or similar; 6. Strong understanding of model performance monitoring, drift detection, and retraining workflows; 7. Upper-Intermediate English level. BENEFITS 1. Professional growth: Accelerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps. 2. A selection of exciting projects: Join projects with modern solutions development and top-tier clients, including Fortune 500 enterprises and leading product brands. 3. Flextime: Tailor your schedule for an optimal work-life balance, with options to work from home or in the office—whatever makes you happiest and most productive. Your application will be evaluated based on your qualifications and experience. We look forward to reviewing your application.