Design, implement and maintain ML pipelines for model training, validation, and deployment

Automate model training, testing and deployment (CI/CD of ML models)

Monitor model performance, data drift, and system health in production environments.

Deploy models in pre-prod, prod environments.

Collaborate with data scientists to operationalize machine learning models and algorithms

Implement version control for models, datasets, and ML experiments using MLOps tools

Optimize ML infrastructure for scalability, reliability, and cost-effectiveness

Troubleshoot and resolve issues related to model deployment and production systems

Maintain documentation for ML workflows, deployment processes, and system architecture

This position may require availability outside of standard business hours ...