Senior ML Ops Engineer Join our company as a Senior Machine Learning Operations (MLOps) Engineer to work on cutting-edge projects involving AI and machine learning. In this role, you will be responsible for deploying and managing ML workflows in production environments. Responsibilities: - Design and implement frameworks for detecting data and model drift, ensuring continuous monitoring and high reliability of ML models in production. - Develop model calibration frameworks and establish versioning practices to maintain transparency and reproducibility across the ML lifecycle. - Build tools for model performance monitoring, operational analytics, and drift mitigation, ensuring reliable operation in production environments. - Collaborate with cross-functional teams, including engineering, product, and data science, to integrate MLOps best practices into our software development life cycle. Requirements: - 3+ years of experience in MLOps, ML Engineering, Data Engineering or related roles, focusing on deploying and managing ML workflows in production environments. - 5+ years of experience using Python. - Proficient in using 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. Benefits: - Professional growth: Accelerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps. - Competitive compensation: We match your ever-growing skills, talent, and contributions with competitive USD-based compensation. - A selection of exciting projects: Join projects with modern solutions development and top-tier clients that include Fortune 500 enterprises and leading product brands. - Flextime: Tailor your schedule for an optimal work-life balance, by having the options of working from home and going to the office.