Associate MLOps Analyst
Posted On: 08-01-25
job description job description Job Title Associate MLOps Analyst Direct Supervisor Data Science Manager Function Data & Analytics External Interfaces Internal Interfaces Job Requirements Education Relevant Experience Behavioural Skills Knowledge algorithms, OOPs information retrieval or recommendation systems Roles & Responsibilities Engineering Development and Integration 1. Collaborate with data scientists to deploy ML models into production environments 2. Implement and maintain CI/CD pipelines for machine learning workflows 3. Use version control tools (e.g., Git) and ML lifecycle management tools (e.g., MLflow) for model tracking, versioning, and management. 4. Design, build as well as optimize applications containerization and orchestration with Docker and Kubernetes and cloud platforms like AWS or Azure Automation & Monitoring 5. Automating pipelines using understanding of Apache Spark and ETL tools like Informatica PowerCenter, Informatica BDM or DEI, Stream Sets and Apache Airflow 6. Implement model monitoring and alerting systems to track model performance, accuracy, and data drift in production environments. Collaboration and Communication 7. Work closely with data scientists to ensure that models are production-ready 8. Collaborate with Data Engineering and Tech teams to ensure infrastructure is optimized for scaling ML applications. Optimization and Scaling 9. Optimize ML pipelines for performance and cost-effectiveness Operational Excellence 1. Help the Data teams leverage best practices to implement Enterprise level solutions. 2. Follow industry standards in coding solutions and follow programming life cycle to ensure standard practices across the project 3. Helping to define common coding standards and model monitoring performance best practices 4. Continuously evaluate the latest packages and frameworks in the ML ecosystem 5. Build automated model deployment data engineering pipelines from plain Python/PySpark models/codes Stakeholder Engagement 1. Collaborate with Data Scientists, Data Engineers, cloud platform and application engineers to create and implement cloud policies and governance for ML model life cycle.
: Associate MLOps Analyst
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