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Machine Learning Engineer

Build intelligent systems that learn and adapt

Overview

Machine Learning Engineers build and deploy ML models that power AI applications. They bridge the gap between data science and software engineering, focusing on making models production-ready. ML/AI is one of the fastest-growing and highest-paying tech fields.

Skills Required

Technical Skills

  • Python (NumPy, Pandas, Scikit-learn)
  • Deep learning (TensorFlow, PyTorch)
  • Machine learning algorithms
  • Feature engineering
  • Model deployment (MLOps)
  • Cloud ML services
  • Data pipelines
  • Model monitoring

Soft Skills

  • Analytical thinking
  • Research mindset
  • Business understanding
  • Communication
  • Problem formulation

Interview Tips

1

Be strong in ML fundamentals - algorithms, math

2

Prepare for coding problems in Python

3

Know how to take models from notebook to production

4

Explain complex ML concepts simply

5

Have projects demonstrating end-to-end ML

Common Interview Questions

Explain gradient descent and its variants

How do you handle class imbalance?

What's the difference between bagging and boosting?

How would you deploy a model at scale?

Describe an ML project you've worked on

Career Path

ML Engineer → Senior ML Engineer → Staff ML Engineer → Principal ML Engineer → Director of ML

Salary Range

₹10-50 LPA (India) | $120,000-$250,000 (US)

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