చిట్కా: 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.
ఈ కెరీర్ పాథ్కి సంబంధించిన, AIshala ద్వారా చేసిన ఉచిత Courses. మొత్తం సమయం: 6 వారాలు.