MLOps Engineer Career Roadmap 2026
MLOps Engineers own the path from notebook to production — automated pipelines, model versioning, deployment, monitoring, and retraining. It is one of the highest-demand roles in AI job markets from the US to India.
What you need to know
- ✓DevOps fundamentals: Linux, Git, CI/CD, containers
- ✓ML pipeline orchestration: Kubeflow, Airflow, MLflow
- ✓Model serving: TensorFlow Serving, TorchServe, Triton
- ✓Infrastructure: Kubernetes, Terraform, cloud (AWS/Azure/GCP)
- ✓Observability: drift detection, performance monitoring, alerting
Step-by-step learning path
Follow these phases in order. Each builds on the previous.
DevOps Base
Month 1–2Skills to learn
Build these projects
- →CI/CD pipeline for a web app
- →Multi-container Docker Compose setup
ML Pipelines
Month 2–4Skills to learn
Build these projects
- →Automated training + registration pipeline
- →Hyperparameter tuning workflow
Kubernetes for ML
Month 4–6Skills to learn
Build these projects
- →Deploy model on EKS/GKE
- →Auto-scaling inference service
Production MLOps
Month 6–8Skills to learn
Build these projects
- →Full MLOps platform with monitoring
- →Automated retraining on drift
Tools & technologies
Frequently asked questions
Can a DevOps engineer transition to MLOps?+
Yes — DevOps engineers are the fastest to transition. You already know containers, CI/CD, and Kubernetes. Add MLflow, model serving, and drift monitoring — typically 3–4 months of focused learning.
Best MLOps course in India?+
Look for live cohorts with hands-on labs, capstone projects, and job support. Rajinikanth Vadla's MLOps Masterclass covers DevOps through MLOps, LLMOps, and AI Agents in 4–5 months with 150+ hours of labs.
Ready to follow this roadmap with guidance?
Rajinikanth Vadla's live cohorts cover the skills in this roadmap with hands-on labs, capstone projects, and 1-on-1 mentorship.
Want this MLOps Engineer roadmap turned into your own plan?
A roadmap shows the destination. In 1:1 mentorship I turn it into a week-by-week learning path for your background, review your projects, and prepare you for interviews until you land the role. Online, in your time zone.
Start with one 60-minute 1:1 call: .
Prefer a structured live course? Join the MLOps · AIOps · LLMOps · Agentic AI masterclass →