Machine Learning Engineer Salary in India

Summary: Machine Learning Engineers in India earn between ₹3.0 to ₹22.1 Lakhs annually. They drive innovation, make critical decisions with minimal human intervention, and enjoy high industry demand.

Introduction

Machine Learning is a branch of Artificial Intelligence and computer science that uses data and algorithms to imitate how humans learn and improve accuracy. It is becoming increasingly popular and crucial for effective productivity and decision-making processes in today’s market. 

Moreover, pursuing a career in Machine Learning may open many job opportunities for you. Significantly, Machine Learning Engineers are becoming highly in demand in the market with lucrative salaries. The following blog post will evaluate Machine Learning Engineer Salary in India along with the roles, responsibilities and skills required.

What is Machine Learning?

Machine learning is a branch of artificial intelligence where computers learn from data and improve their performance without explicit programming. Algorithms process large datasets to identify patterns, make decisions, and predict outcomes. This technology powers various applications, from recommendation systems and fraud detection to self-driving cars and speech recognition. 

Engineers train models using techniques like supervised, unsupervised, and reinforcement learning. Exposing models to more data improves their accuracy and efficiency. Machine learning’s ability to automate complex tasks and adapt to new information drives innovation across industries, transforming how we interact with technology and solve real-world problems.

Why is Machine Learning Important?

Machine Learning solves complex mathematical calculations with automation for Big Data. Consequently, Machine Learning helps businesses identify critical patterns within a dataset and ensures better decisions with less human intervention. 

Moreover, Machine Learning makes it possible to conduct timely analysis and assessment of organisational strategies and make real-time predictions. This process helps in effective decision-making and transforms industries, opening up opportunities for millions of Machine Learning Engineers.

What Does a Machine Learning Engineer Do?

The role of a Machine Learning Engineer is quite similar to that of a Data Scientist, as both involve working with large volumes of Data. One significant similarity between both roles is that you need excellent Data Management skills to manage and deal with such large datasets. 

Machine Learning Engineers mainly focus on designing self-running software essential for predictive model automation. Effectively, they collaborate closely with data scientists to ensure that the data used by the latter is more accurate. Let’s briefly look at the key responsibilities of a Machine Learning Engineer.

Key responsibilities of a Machine Learning Engineer:

• Studying and Converting Data Science Prototypes.
• Designing and Developing Machine Learning systems and schemes.
• Perform statistical analysis and fine-tune models using the test results.
• For training, Machine Learning Engineers need to find datasets online.
• Training and retraining ML systems and models.
• Extending and enriching existing ML frameworks and libraries.
• Developing Machine Learning apps based on the customer/client needs.
• Research, experiment and implement suitable ML algorithms and tools.
• Analysing problem-solving capabilities and use cases of ML and ranking them by their probability of success.
• Exploring and visualising data for better understanding and identifying differences in data distribution that can affect model performance. 

Skills Needed to Become a Machine Learning Engineer

To excel as a Machine Learning Engineer, you need to have the right skills that will enable you to work with more excellent proficiency. Following are the skills necessary to learn Machine Learning:

Statistics and Probability: understanding algorithms is one of the most crucial aspects of becoming a Machine Learning Engineer. You must have complete knowledge of theories involving Hidden Markov models, Naïve Bayes and Gaussian Mixture.

Data Evaluation and Modelling: evaluating the effectiveness of the different Machine Learning models at regular intervals is one of the crucial tasks. You can do this by developing your skills in regression and classification, measuring the error or accuracy of a given model. Consequently, you also need an evaluation strategy to help the process.

ML Algorithms: it is essential that when you pursue a career as a Machine Learning Engineer, you know different ML algorithms. You should know which algorithm perfectly fits a particular situation. Understanding these subjects requires knowledge of partial differential equations, gradient descent, quadratic programming and others.

Programming languages: Expertise in programming languages is one of the most crucial skills for an excellent career in Machine Learning. It includes learning Python, R, Java, C++, SQL, etc. These languages help you in different stages of machine learning projects.

Factors Affecting Machine Learning Engineer Salary in India

The demand for Machine Learning Engineers is high in the market. However, you need to have the adequate and right number of skills to get the job. Accordingly, those with the right skill sets are in higher demand, which is one of the biggest reasons for India’s high Machine Learning salary.

There are various factors affecting the salary of a Machine Learning Engineer in India, which include:

• The first factor is the company that you work for. In India, companies like Facebook, Google, Apple, Salesforce, etc., offer higher job opportunities and salaries for ML Engineers.
• Another factor is the candidate’s experience because the more experience you have, the more your skills and knowledge are refined. Accordingly, an entry-level ML Engineer will earn around 5.1 LPA. In contrast, a Senior ML Engineer in India with ten years of experience will earn more than 20 Lacs annually.
• The location of the candidate or the company also matters because the location impacts the ML salary. It mainly occurs because of the differences in infrastructure and lifestyle expenses required for a Machine Learning Engineer.
• The candidate’s skills are another critical factor affecting the ML Engineer’s salary. Significantly, it requires the ability to use your skills effectively. The skills of the candidate determine the wages in India.

Machine Learning Engineer Salaries in India by Cities 

According to AmbitionBox, the salary for a Machine Learning Engineer in India ranges from ₹3.0 Lakhs to ₹22.1 Lakhs, with an average annual wage of ₹10.1 Lakhs. 

Similarly, Glassdoor reports that Machine Learning Engineer salaries in India span from ₹3.0 Lakhs to ₹22.1 Lakhs, with the average being ₹10.1 Lakhs per year. However, the salary of a Machine Learning Engineer varies in different cities. These are as follows: 

Bangalore: On average, Machine Learning Engineer salaries in Bangalore stand at ₹855,64 per annum. 

Hyderabad: According to Glassdoor reports, the average salary of a Machine Learning Engineer is ₹898,459. 

Chennai: the annual Machine Learning Engineer salary in India in Chennai is ₹671,599 as per the reports of Payscale. 

Mumbai: Glassdoor records the average salary of a Machine Learning Engineer in Mumbai being ₹855,000 per annum. 

Pune: In Pune, the average annual salary of ML Engineers stands at ₹601,373 as per PayScale.

Delhi: According to Indeed, the yearly wage of ML Engineers, on average, stands at ₹465,697 per annum. 

Machine Learning Engineer Job Opportunities

Machine Learning Engineer job opportunities are abundant, spanning various industries such as technology, finance, healthcare, and e-commerce. Moreover, roles in this field are highly sought after due to their pivotal role in advancing AI applications. Demand for skilled professionals is high, offering competitive salaries and the chance to work on cutting-edge innovations. In India, numerous roles are available for those with ML skills:

Machine Learning Engineer: Design and develop machine learning models and algorithms.

Data Scientist: Analyse and interpret complex data to provide insights and solutions.

Data Engineer: Build and maintain data pipelines and architecture.

Data Analyst: Examine data sets to identify trends and draw actionable conclusions.

Software Developer/Engineer: Integrate machine learning models into software applications.

Human-Centred Machine Learning Designer: Focus on creating user-friendly ML applications.

NLP Scientist: Develop algorithms for processing and understanding human language.

Director of Analytics: Oversee data analysis projects and guide the analytics team.

Principal Data Scientist: Lead research and development in data science projects.

Computer Vision Engineer: Work on image and video analysis technologies.

Algorithm Engineer: Create and optimise algorithms for various applications.

Research Scientist: Conduct advanced research in machine learning and related fields.

AI Specialist: Develop and implement artificial intelligence solutions.

Robotics Engineer: Apply machine learning techniques to robotics and automation.

Deep Learning Engineer: Specialises in neural networks and deep learning algorithms.

Big Data Engineer: Manage and analyse large-scale data sets using ML techniques.

Quantitative Analyst: Use ML financial and statistical analysis models.

Business Intelligence Developer: Create data-driven solutions for business insights.

Predictive Modeler: Develop models to predict future trends and behaviours.

Recommendation Systems Engineer: Design and implement personalised recommendation algorithms for e-commerce and streaming services platforms.

Frequently Asked Questions

What is the average Machine Learning Engineer salary in India?

The average Machine Learning Engineer salary in India varies widely, ranging from ₹3.0 Lakhs to ₹22.1 Lakhs per year. Factors influencing this range include the engineer’s experience level, specific skill sets, and employment location. Major tech companies tend to offer higher salaries.

Why is machine learning meaningful for businesses?

Machine learning is crucial for businesses because it automates complex tasks, enhances decision-making, and provides real-time predictive insights. By analysing large datasets, machine learning helps companies identify trends, optimise operations, and improve customer experiences, ultimately driving innovation and increasing competitive advantage.

What are the critical responsibilities of a Machine Learning Engineer?

Key responsibilities of a Machine Learning Engineer include designing and developing machine learning systems, performing statistical analysis, fine-tuning models, training and retraining models, collaborating with data scientists, and developing ML applications tailored to client needs. They also explore and visualise data to improve model performance.

Conclusion

Thus, machine learning is an integral part of business organisations worldwide and is where effective decision-making can occur. Machine Learning Engineers are henceforth in demand in India to endure higher productivity. 

Consequently, Machine Learning Engineer salaries in India remain high, although variations occur given differences in skills and experience. While it is one of the collaborative job roles, the demand for ML Engineers makes it one of the highest-paying jobs in the country.