Assistant Manager, ML OPS

Infrastructure Design and Implementation:

Design and build scalable infrastructure for deploying and managing machine learning models in production environments.

Implement CI/CD pipelines to automate model deployment and updates.

Automation and Optimization:

Develop automation scripts and tools to streamline the ML pipeline, improving efficiency and reducing manual intervention.

Optimize models for performance, scalability, and cost-effectiveness.

Collaboration and Support:

Collaborate with cross-functional teams to understand model requirements and provide infrastructure support.

Work closely with data scientists and software engineers to ensure smooth integration of ML models into production systems.