Role Overview
A MLOps Engineer is a professional who has several years of experience in MLOps and is expected to lead or independently manage large-scale projects related to ML model deployment, monitoring, and optimization. They also have a deeper understanding of systems architecture and can mentor junior team members.
Responsibilities
- Lead and design the architecture for deploying and maintaining ML models in production.
- Implement robust, scalable, and secure ML pipelines and workflows.
- Work closely with development teams to deploy and integrate models.
- Ensure the system is optimized for high availability, reliability, and performance.
- Automate end-to-end model deployment processes and CI/CD pipelines.
- Implement monitoring and alerting for production models, ensuring uptime and performance.
- Conduct performance tuning and model updates based on real-time data and feedback.
- Manage infrastructure on cloud services and container orchestration systems like Kubernetes.
- Mentor junior MLOps engineers and interns, providing technical guidance and reviews.
