ML Ops - 14th Jul (Tuesday) - Virtual Interview- 6+years

Job description

**MLOps** **Engineer** Required Technical Skill Set **PyTorch, TensorFlow, Scikit-learn, Visualization and Reporting Tools (e.g., Power BI, Tableau/Qlik Sense), SAS schedulers/Jobs** **Must-Have** - PyTorch, TensorFlow, Scikit-learn - Visualization and Reporting Tools (e.g., Power BI, Tableau/Qlik Sense) - SAS schedulers/Jobs - Design, develop and maintain dashboards and reports using tools like Power BI, Tableau, Qlik Sense, SSRS - Optimize SAS jobs, Develop and maintain changes to SAS code - Design, develop and maintain dashboards and SAS reports - Support and administer enterprise-scale analytics delivery with platform administration skills across SAS and Power BI - Implement CI/CD pipelines for data workflows and analytics applications in AI/ML frameworks (PyTorch, TensorFlow, Scikit-learn) and building end-to-end ML pipelines - Model deployment, training, validation, monitoring, and orchestration on any cloud platforms (AWS, Azure, or GCP) - Deploy and monitor ML models across environments - Provide regular updates on progress and align deliverables with business objectives. - Partner with Data Scientists, Analysts and Platform teams to translate requirements into operational solutions; maintain documentation for deployments, monitoring, access, and support procedures.