Machine Learning Engineer Salary in Indi

Machine Learning Engineer Salary in India How Much Does one Earn

Machine Learning Engineer Salary in India - How much does one earn?

The massive hype surrounding Data Science and AI has driven the role of Machine Learning Engineers into existence. It has become a critical part of these multidisciplinary domains, and it is now a well-paid and highly sought-after profession. Let’s review the Machine Learning Engineer salary in India.

Every industry works with massive amounts of knowledge. This fuelled the popularity and acceptance of Machine Learning technology and its value in terms of its application and therefore the future which will be shaped with it. Thus, the necessity for expertise during this domain catapulted, which resulted in it being one among the foremost popular career choices within the world today.


Importance of Machine Learning

Machine Learning algorithms are not really new to the scene. However, the automation of complex mathematical calculations for the purpose of big data is only a recent development. Considering that, Machine Learning has increasingly become more effective, quicker, and optimized over the years. Better performance means enterprises can improve their functioning and productivity and, along with it, have better decision-making.


Machine Learning helps businesses expose critical patterns within the data and make better decisions with minimum human intervention. Apart from this, it is ideal for the timely analysis and assessment of organizational strategies and real-time predictions and, in the process, transforming industries. This, in turn, opens up opportunities galore for Machine Learning Engineers.


What does a Machine Learning Engineer do?

Machine Learning Engineers implement programming frameworks and large Data tools for transforming data into scalable Data Science models. They feed the info into the models that are worked on by Data Scientists and also upgrade theoretical Data Science models to production-level models. These models can work with enormous sizes of real-time data. These tasks involve close collaborations with Data Scientists. Machine Learning Engineers also are capable of building programs that control robots and computers. The developed algorithms allow machines to uncover patterns within the programming data. They learn to know commands and eventually make intelligent decisions and perform tasks without human intervention.

Why is the demand for Machine Learning Engineers increasing?

The demand for Machine Learning Engineers is more than Data Scientists.

The global Machine Learning market is predicted to reach US$20.83 billion in 2024 – Forbes

In light of the growing competition in the global market, companies are hiring talented Machine Learning Engineers. The indispensable nature of a Machine Learning job ensures that the professionals working in related roles receive a hefty sum as compensation for their skills.

Required Skills of a Machine Learning Engineer

Applied Mathematics

In Machine Learning, mathematics is used in various ways as follows:

  • Using mathematical formulas for choosing the correct Machine Learning algorithms

  • Approximation of confidence levels

  • Setting parameters

Some of the important mathematics topics applied in Machine Learning are:

  • Statistics

  • Probability

  • Linear algebra

  • Multivariate calculus

  • Different distributions such as Poisson, binomial, normal, etc.

Apart from math, some physics concepts are also applicable in Machine Learning.

Fundamentals of Computer Science and Programming

Every good Machine Learning Engineer is expected to have a fundamental understanding of computer science and knowledge in programming. Computer science concepts include:

  • Algorithms (dynamic programming, greedy programming, searching, sorting, etc.)

  • Data structures (queue, stack, graph, tree, etc.)

  • Space and time complexity and more

Programming concepts in Machine Learning include:

One should also be familiar with Python libraries such as Scikit-Learn, NumPy, Pandas, TensorFlow, Matplotlib, etc.

Machine Learning Algorithms

It goes without saying that Machine Learning algorithms are an essential part of the domain. Some of the common Machine Learning algorithms are:

  • Naïve Bayes classifier

  • Support Vector Machine (SVM)

  • K-means clustering

  • Apriori algorithm

  • Decision trees and random forests

  • Linear and logistic regression

Data Modeling and Data Evaluation

Data Modeling requires the understanding of underlying data structures and discovering patterns that are otherwise hard to note . Then comes data evaluation, which uses an algorithm that's right for the info . A good Machine Learning Engineer will know everything about the various algorithms that contribute to effective data modeling and data evaluation.

Neural Networks

While it is not mandatory to know all the details of neural networks, a core understanding is definitely important for Machine Learning Engineers. Neural networks are modeled after neurons and consist of multiple layers:

  • Input layer

  • Multiple hidden layers

  • Output layer

Data passes through these layers and demonstrates a deep perspective into the parallel computations as well as sequential computations that are further used for data analysis or learning.

Following are some of the different types of neural networks:

  • Radial basis function neural network

  • Feedforward neural network

  • Modular neural network

  • Convolutional neural network

  • Recurrent neural network

Natural Language Processing (NLP)


Natural Language Processing essentially tries to show the complexities of human language to computers for them to interpret and understand human communication better. In conjunction with Machine Learning algorithms, NLP builds systems that learn to perform tasks by themselves and obtain better through experience. NLP-powered tools can help one identify sentiment, extract named entities from text, and lots of other things. Language translators, chatbots, spell-checkers, etc. are all samples of NLP applications. Different libraries with different functions form the inspiration of NLP.

Communication Skills

While soft skills may usually not be considered that important, it makes a world of difference in a career trajectory. As much as it is vital to be able to generate insights from data, it is important to know how to communicate these findings to someone who is not as knowledgeable in the technical field, such as members of other teams, clients, and shareholders.

In a nutshell, here is what a typical Machine Learning Engineer is expected to be skilled in:

  • Programming in Java and Python

  • Knowledge of math and probability

  • Strong understanding of algorithms and statistics

  • Software architecture, data modeling, and data structures

  • Prior experience with frameworks

  • Good communication skills and teamwork

  • A degree in computer science, mathematics, or similar fields or equivalent qualification

Roles and Responsibilities of a Machine Learning Engineer

The roles and responsibilities of a Machine Learning Engineer include the following:

  • Performing statistical analysis

  • Fine-tuning of test results

  • Training and retraining of systems

  • Working on frameworks

  • Undertaking ML experiments and tests

  • Designing ML programs

  • Building Deep Learning systems for various use cases based on business requirements

  • Implementing suitable AI/ML algorithms


Machine Learning Job Roles

Here are the various job roles available for certified experts in the field:

  • Machine Learning Engineer

  • Data Scientist

  • Data Engineer

  • Data Analyst

  • Software Developer/Engineer (AI/ML)

  • Human-centered Machine Learning Designer

  • NLP Scientist

  • Director of Analytics

  • Principal Data Scientist

  • Computer Vision Engineer

  • Algorithm Engineer

  • Computer Scientist

 Machine Learning Engineer Job Opportunities

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According to LinkedIn, there are over 19,000 Machine Learning Engineer jobs in India alone.

  • Bangalore: There are 7,000+ Machine Learning Engineer jobs in Bangalore.

  • Hyderabad: There are over 2,100 Machine Learning Engineer jobs in Hyderabad.

  • Chennai: There are 500+ Machine Learning Engineer jobs in Chennai.

  • Mumbai: There are over 1,300 jobs for Machine Learning Engineers in Mumbai.

  • Pune: There are 1,800+ jobs for Machine Learning Engineers in Pune.

  • Delhi: 730+ Machine Learning Engineer jobs are available in Delhi.

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