MLOps Strategy & Architecture:
- Collaborate on the MLOps strategy for our cloud environment, ensuring alignment with business objectives, security requirements, and best practices.
- Collaborate on the technical design of a MLOps platform that provides a self-service approach to the MLOps loop problems, such as data ingestion, feature engineering, model training, model validation, model deployment, model monitoring.
- Develop and maintain comprehensive documentation for MLOps processes and infrastructure.
Hybrid ML-loop Implementation:
- Design and implement Infrastructure as Code (IaC) solutions for provisioning and managing cloud resources using Terraform.
- Implement robust security measures to protect sensitive data, ML models, and other artefacts.
- Implement new functionalities while ensuring key non-functional properties of the model development toolchain, particularly reproducibility.
- Implement monitoring dashboards and alerts to proactively identify and resolve MLOps platform issues.
• Collaboration & Leadership:
- Work closely with ML engineers, data scientists, software engineers, and infrastructure teams to deliver a high-quality MLOps solution.
- Communicate effectively with stakeholders at all levels, including technical and non-technical audiences.
- Stay up to date with the latest MLOps trends and technologies and adopt new approaches.
- Participate in code reviews and contribute to the development of best practices