MLOps Engineer with Domino Experience

Key Responsibilities Platform Operations & Monitoring • • Monitor ML model endpoints and overall platform health using tools like Grafana and Domino Data Lab. • • Respond to incidents and alerts, perform code fixes, manage incidents internally and manages changes through ServiceNow • • Interface directly with Domino Data Lab support to resolve model platform-related issues. Model Deployment into Production • • Deploy and Maintain ML models in production environments. • • Ensure models are properly integrated into automated pipelines and meet standards. Pipeline Maintenance • • Collaborate with data scientists and engineers to ensure smooth handoff from model development to production. • • Maintain and support ML pipelines, ensuring stability and scalability. • • Continuously optimize pipeline performance, resource usage, and automation Automation & Tooling • • Implement automation for deployment and monitoring tasks. • • Contribute to platform improvements. Required Skills & Experience • • Extensive experience in Python programming • • Strong experience with ML model deployment and production monitoring. • Working knowledge of core data science concepts, such as model evaluation metrics, overfitting, data drift, and feature importance. • Proficiency in AWS services (like S3, RedShift etc) • Experience with Grafana for monitoring and alerting. • Good to have hands-on experience with Domino Data Lab platform. • Solid understanding of CI/CD pipelines, version control, containerization, and orchestration. • Ability to communicate effectively with internal and external stakeholders. • Excellent troubleshooting and incident management skills.