Track 03 · Data & AI

Machine Learning Engineer

Productionize machine learning models at scale.

  • ₹8–18 LPAEntry salary
  • ₹28–60 LPASenior / Lead
  • Very HighDemand outlook

What does this role do?

ML Engineers focus on taking research models into production environments.

Model Deployment

Deploy models using Docker and cloud services.

MLOps

Build CI/CD pipelines for ML workflows.

Skills required

PythonTensorFlowPyTorchMLOpsKubernetesAWS SageMaker

Career overview

  • Productionize machine learning models at scale.
  • Best suited for people who enjoy Python, TensorFlow, and PyTorch and want to build solutions that create visible impact in real teams.
  • Typical work includes deploy models using docker and cloud services and build ci/cd pipelines for ml workflows.
  • Demand is Very High in India, with entry salaries around ₹8–18 LPA and experienced Machine Learning Engineer roles often reaching ₹28–60 LPA.
  • Hiring teams value practical projects, clear problem-solving, and collaboration — not just certificates or tool lists.
  • Start with ML Fundamentals, then strengthen Deep Learning, and keep improving MLOps through hands-on projects, internships, and production-like assignments.

Learning path & roadmap

Stage 1

ML Fundamentals

Supervised and unsupervised learning.

Stage 2

Deep Learning

Neural networks and frameworks.

Stage 3

Production Systems

MLOps and scaling.

Certifications

AWS Certified Machine Learning

Specialty certification.

Required tools

JupyterMLflowDockerKubernetes

Salary progression (India)

LevelExperienceAnnual CTC
Junior0–2 yrs₹8–18 LPA
Senior5+ yrs₹28–60 LPA

Typical fresher vs. industry expectation

MLOps
70%

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