Quick பதில்: MLOps Engineers manage ML models in production for companies like Razorpay and Indian AI startups, earning ₹1L–₹7.5L/mo. You'll master Kubernetes, MLflow, and CI/CD pipelines to deploy, monitor, and automate the entire ML lifecycle reliably at scale.
Your morning might begin reviewing model performance dashboards: has accuracy drifted overnight? You investigate, then deploy a retraining pipeline to an auto-scaling Kubernetes cluster. By lunch, you're debugging a data validation failure in the ETL pipeline and coordinating with the data team. Afternoon brings a code review for a colleague's CI/CD pipeline changes, followed by a design discussion about versioning strategies for a new computer vision model. You document the architecture, test it locally with Docker, and prepare for Friday's production rollout.
The work is collaborative: you ship what data scientists build, support what engineers deploy, and ensure what customers use remains stable and fast.
MLOps is one of India's fastest-growing specializations. Entry-level roles (2–3 years) typically involve managing training pipelines and basic Kubernetes deployments at companies like Flipkart, Swiggy, or Unacademy. Mid-level roles (4–6 years) focus on architecture and scaling—handling terabytes of data and thousands of concurrent predictions. Senior MLOps engineers drive strategy: selecting tools, mentoring teams, and building platforms that support dozens of models across the organization. Remote roles and contracting are common, and compensation aligns with senior backend engineering bands.
இந்த career path-க்கு match ஆகுற AIshala curated free courses — order-ல கொடுக்கப்பட்டிருக்கு. மொத்த prep time: 6 வாரங்கள்.