MLOps Engineer Interview Prep

Builds and maintains the infrastructure that keeps ML models running correctly in production — retraining pipelines, drift monitoring, versioning, and rollback systems.

Topics

MLOps

Keeping ML models running correctly in production: versioning, retraining, monitoring, and serving infrastructure.

Machine Learning Fundamentals

Core ML concepts interviewers probe for: model families, evaluation, and the training practices behind them.

CI/CD & DevOps

Automating the path from commit to production: pipelines, containers, deployment strategies, and GitOps.

Cloud Infrastructure & Architecture

Designing resilient, secure, cost-efficient systems on cloud infrastructure — networking, high availability, and infrastructure as code.