Machine Learning Engineer Salary in India in 2025.

Machine learning (ML) has become one of India’s highest-paying careers, with salaries in 2025 ranging from INR 6 LPA for freshers to INR 50 LPA or more for experienced professionals. This variation is driven by factors like experience, skillset, and industry, as ML demand grows across sectors such as healthcare, finance, and e-commerce.

In this blog, we’ll explore the key factors influencing the machine learning engineer salary in India, including industry trends, location, skillset, and experience levels.

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Machine Learning Engineer Salary in India: An Overview

The demand for machine learning engineers in India has soared over the past few years, and 2025 is expected to witness even more significant growth. In fact, the global machine learning market is expected to reach $225.91 billion by 2030 growing at a CAGR of 36.2%, as per business fortune insights.

The surge in machine learning applications across sectors has created immense career opportunities. To equip yourself with the skills needed to thrive, check out these top ML courses.

• Masters in Artificial Intelligence and Machine Learning
• Executive Diploma in Machine Learning and AI
• Executive Programme in Generative AI for Leaders

Machine learning engineers develop systems that learn from data, make decisions, and optimize operations across sectors like healthcare, automotive, tech, and finance. These roles are no longer confined to just tech companies; they now span industries that are embracing AI to revolutionize their services.

Now, let's dive deeper into how machine learning engineer salary figures vary based on specific roles.

Machine Learning Engineer Salary in India: Experience-Based Breakdown

As a machine learning engineer, your salary can vary significantly depending on your level of experience, expertise, and specific responsibilities. The compensation you can expect will directly correlate with these factors.

To provide a clearer picture, let’s break down the salary figures according to different experience levels within the machine learning engineering field.

Source: Glassdoor

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Also Read: Top 10 Highest Paying Machine Learning Jobs in India [A Complete Report]

While roles define your pay, industries also play a major part in determining your machine learning engineer salary. Let's explore the salary variations across key sectors.

Machine Learning Engineer Salary in India: Industry Insights

The demand for machine learning engineers is growing across various industries. The skills and expertise of these professionals are crucial for businesses to stay competitive and innovate.

Industries like healthcare, automotive, and tech are rapidly adopting AI and machine learning technologies to streamline operations and offer advanced solutions. As these sectors continue to expand, so do the opportunities and salaries for machine learning engineers.

Now, let’s take a deeper dive into the industry-specific salary breakdowns to understand where the most lucrative opportunities are.

Source: Ambition Box

Also Read: AI Engineer Salary in India: 2025 Guide for Beginners & Experienced in 2025

Having seen the salary breakdown by industry, it’s time to dive into how geographical location impacts the earning potential for machine learning engineers across major Indian cities.

Machine Learning Engineer Salary in India: Differences by Location

Machine engineer salary can vary depending on the location within India. Cities with major tech hubs like Bengaluru, Hyderabad, Pune, and Mumbai tend to offer higher salaries due to the concentration of tech companies and innovation-driven startups.

Let’s look at how machine learning engineer salaries differ across five key Indian cities.

Before checking the table, keep in mind that cities with higher living costs and a concentration of major companies usually provide more competitive salaries to attract talent.

Source: Ambition Box

Also Read: Top 7 Career Options in Machine Learning & Cloud

Although city-specific factors affect your salary, the organization you join can elevate your earnings further. Let’s take a closer look at what some of the top recruiters are offering.

Machine Learning Engineer Salary in India: By Recruiters

When it comes to salaries, the company you work for plays a significant role. Global tech giants, Indian unicorns, and specialized AI firms offer different compensation packages based on their market positioning and budget.

Some of the leading companies in the Indian tech ecosystem consistently offer competitive salaries for machine learning engineers. 

Here’s a quick look at how salaries stack up across top companies hiring machine learning engineers.

Source: Ambition Box

These leading companies offer exceptional salary packages, but startups and mid-size firms also pay competitive salaries to attract top talent.

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Also Read: Top Artificial Intelligence Jobs in 2025: Roles and Salary

Factors That Influence Machine Learning Salaries in India

Machine learning engineer salary in India is shaped by a combination of factors that can influence both the pay scale and career growth. While some factors, like industry and location, are more obvious, others, like certifications and company size, might have subtler effects on salary potential. 

Let's discuss each of these factors and explore how they impact your earnings in the machine learning field.

Industry

The industry in which you work plays a pivotal role in shaping your salary as a machine learning engineer. Various sectors adopt machine learning technologies for different purposes, and they each value specific skills, which directly affect compensation.

• IT and Software: This sector focuses on AI automation, AI-driven software, chatbots creation, and predictive models. It remains one of the highest-paying fields for machine learning engineers due to its rapid adoption of AI and continuous innovation. Large tech companies and startups alike are eager to integrate AI into their products, driving demand for skilled engineers.
• Healthcare: Machine learning in healthcare is growing exponentially, particularly in diagnostics, predictive analytics, and optimizing patient care. The healthcare industry requires engineers to develop models that can process medical data, predict diseases, and optimize treatment plans. These roles demand not only technical proficiency but also domain-specific knowledge, influencing the salary structure. 
• Finance: In finance, machine learning is employed for fraud detection, algorithmic trading, credit scoring, and risk management. ML engineers in this sector work with large datasets and high-stakes predictions, making these positions some of the most lucrative in the industry. Financial institutions are willing to pay top salaries for engineers who can help them gain an edge in the highly competitive market.
• Automotive and Manufacturing: The automotive industry, especially with the rise of autonomous vehicles, offers significant opportunities for machine learning engineers. ML in manufacturing is focused on predictive maintenance, supply chain optimization, and robotics. The demand for expertise in computer vision, sensors, and AI-based automation is growing, further driving salaries in this space.

Example: A machine learning engineer in the healthcare industry might work on developing AI-driven diagnostic tools that can predict diseases, whereas an engineer in the IT sector might focus on creating smart chatbots or recommendation systems for e-commerce platforms.

Location

Location is one of the most immediate factors that can affect the salary of a machine learning engineer. While the cost of living in a particular city often correlates with higher salaries, the concentration of tech companies and industries also plays a crucial role in determining pay.

• Bangalore (Bengaluru): As India's Silicon Valley, Bangalore is home to numerous startups, tech giants, and AI-focused research centers. The city offers the highest-paying machine learning roles, driven by demand from global tech companies and innovation-driven startups. Living costs are also high, but the salary offers more than compensate for this. 
• Mumbai: Known as the financial capital of India, Mumbai offers lucrative opportunities for machine learning engineers, especially in the finance sector. Positions in algorithmic trading, fraud detection, and risk modeling are abundant, making Mumbai a hotspot for high-paying ML roles. 
• Hyderabad and Pune: Both cities are emerging as strongholds for IT companies and tech-driven businesses. Hyderabad is a hub for big data, AI, and IT outsourcing companies, while Pune has a growing startup ecosystem and offers competitive salaries. However, compared to Bangalore and Mumbai, salaries in these cities are typically slightly lower but still competitive in the broader market. 
• Chennai and Delhi NCR: Both cities are experiencing growing demand for machine learning engineers, especially in sectors like retail and government projects. While not as high-paying as Bangalore or Mumbai, these cities are seeing an increase in tech-driven opportunities, leading to more competitive salary offerings.

Example: A fresher working in a tech company in Bangalore may earn a higher salary than a fresher in smaller cities like Bhopal or Lucknow due to the tech ecosystem and availability of specialized opportunities in Bangalore.

Skill Set

Your skill set as a machine learning engineer directly impacts your salary potential. While a foundational understanding of machine learning concepts is essential, having expertise in advanced areas can elevate your earning potential significantly.

• Deep Learning and Neural Networks: Deep learning is critical for developing AI-based solutions such as speech recognition, image recognition, and autonomous vehicles. Professionals skilled in deep learning frameworks like TensorFlow, PyTorch, and Keras are in high demand, leading to higher salaries.
• Natural Language Processing (NLP): NLP is a key technology for chatbots, sentiment analysis, machine translation, and text-based models. If you are proficient in NLP and have experience working on complex language models like GPT or BERT, you’ll find roles that command a premium salary.
• Computer Vision: With the rise of autonomous vehicles, surveillance systems, and augmented reality, computer vision specialists are highly sought after. Engineers with expertise in image processing, object detection, and 3D vision are in demand across sectors like automotive, healthcare, and security.
• Reinforcement Learning: This advanced area of machine learning is used in applications like robotics, AI agents in video games, and automated decision-making. Although not as widely adopted yet, reinforcement learning specialists can command higher salaries due to the advanced nature of the field.
• Big Data and Cloud Computing: A machine learning engineer proficient in big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Google Cloud, Azure) will have a competitive edge in the market. Cloud-based machine learning platforms are becoming standard, so expertise in this area can lead to higher-paying roles. 

Example: A machine learning engineer specializing in deep learning might work on developing advanced speech recognition models for a voice assistant, while someone skilled in NLP could be building the next-generation chatbot for an e-commerce platform.

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Also Read: Types of Machine Learning Algorithms with Use Cases Examples

Certifications

In the rapidly evolving field of machine learning, certifications can significantly boost your employability and salary potential. Specialized certifications show that you possess hands-on experience with the latest tools and technologies, which employers highly value.

• TensorFlow Certification: As one of the most widely used frameworks for machine learning, earning a TensorFlow certification demonstrates your ability to build and deploy machine learning models efficiently.
• AWS Machine Learning Certification: With cloud computing becoming central to machine learning projects, having an AWS certification can set you apart by proving your capability to deploy ML models on cloud infrastructure.
• Python and Data Science Courses: Python remains the most popular programming language in machine learning. Certification in Python or data science platforms like DataCamp or Coursera can open doors to better roles and higher salaries. 
• upGrad Certifications: Platforms like upGrad offer certifications in machine learning and AI, which include real-world projects and industry-relevant skills. These certifications can be crucial when applying to competitive roles in leading companies.

Example: An engineer with an AWS certification might be involved in deploying machine learning models at scale for a cloud services provider, whereas one with a TensorFlow certification could focus on developing deep learning models for a tech company.

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Also read: Top 5 Machine Learning Models Explained For Beginners

Company Size

The size of the company you work for has a significant impact on both salary and career trajectory. Both large corporations and startups offer distinct advantages and challenges when it comes to salary expectations.

• Large Corporations: Multinational companies like Google, Microsoft, and Amazon are known for their high-paying machine learning roles. These organizations often provide excellent benefits, stability, and career growth opportunities. However, the work is typically more structured, and you may be working on larger, well-defined projects.
• Startups: Startups offer dynamic, fast-paced environments where machine learning engineers can work on innovative, high-impact projects. While the base salary may not always be as high as that offered by large companies, stock options and the opportunity to work on cutting-edge technology can provide significant long-term rewards. Moreover, the learning curve in a startup environment is steeper, leading to faster career growth.

Example: In a large corporation like Amazon, you might work on scaling machine learning models for e-commerce personalization, while at a startup, you may be developing AI-powered solutions from the ground up, with more influence over product direction.

Also Read: 5 Breakthrough Applications of Machine Learning

Become an Expert in Machine Learning with upGrad!

To maximize your earning potential as a machine learning engineer in India in 2025, it’s crucial to position yourself in top companies like Google or Amazon that offer competitive salaries. Focus on mastering advanced skills in deep learning, AI solutions, and tools like TensorFlow and PyTorch. 

If you're looking to bridge skill gaps and stay ahead, upGrad’s AI and Machine Learning courses provide expert-led programs and hands-on projects, equipping you with the skills to excel in this high-demand field and boost your career growth.

Here are some of the additional free courses to sharpen your machine learning skills:

• Hypothesis Testing
• Unsupervised Learning: Clustering
• Logistic Regression for Beginners
• Linear Regression - Step by Step Guide
• Introduction to Natural Language Processing

You can also get personalized career counseling with upGrad to guide your career path, or visit your nearest upGrad center and start hands-on training today!

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References:
https://www.researchgate.net/publication/385292480_Research_Paper_Entitled_Application_of_Machine_Learning_Techniques_for_Decision_Making_Process_in_Human_Resource_Management_2023_10th_IEEE_Uttar_Pradesh_Section_International_Conference_on_Electrical_    
https://www.ambitionbox.com/profile/machine-learning-engineer-salary
https://www.glassdoor.co.in/Salaries/machine-learning-engineer-salary-SRCH_KO0,25.htm