Machine Learning Engineer Salary and Top Trends in India: A Comprehensive Guide 

Machine Learning has moved way beyond buzzword status in India. From banks and hospitals to startups and unicorns, companies now want engineers who can build smarter systems, and not just code that runs. And with that demand, salaries are rising fast. But how much does a machine learning engineer’s salary look like in India today?

This blog breaks it all down for you – whether you’re just curious or already eyeing machine learning jobs. We’ll cover the average machine learning engineer salary, what the salary for machine learning engineers with no experience looks like, which cities pay the most, and how acquiring the right skills can lead to a higher machine learning salary. If you’re wondering what an entry-level machine learning engineer’s salary looks like or what to focus on to earn more, you’re in the right place.

What’s the Average Machine Learning Engineer Salary in India?

If you’re curious about earnings, here’s a breakdown based on real-time data from Glassdoor:

• Average Salary: ₹10 lakh per year
  
• Typical Range: ₹7 lakh (entry) to ₹21 lakh (senior) 

Machine learning roles bring competitive pay, especially when compared to similar data positions.

Entry‑Level & Freshers

The average machine learning engineer salary for freshers starts around ₹7 lakh. Some associate roles report an average of ₹8 lakh, aligning well with junior industry standards.

Mid‑Level & Experienced

Mid-career engineers typically fall between ₹10 -15 lakh. Stepping into senior or lead roles can push the range to ₹18 – 49 lakh, depending on the company and specialization, especially in deep learning or AI-heavy positions.

Also Read: Top 10 Steps to Kickstart Your Career as a Machine Learning Engineer

Machine Learning Salary by City in India

Salaries for machine learning engineers can vary quite a bit depending on where you’re based. Cities with a strong presence of tech companies, R&D hubs, and AI-focused startups usually offer better compensation. 

Cost of living also plays a role. Metros like Bengaluru and Hyderabad often offer higher pay. Here’s a breakdown of average and estimated total pay across major Indian cities.

Bengaluru

• Salary Range : ₹8.0 LPA – ₹20.0 LPA
  
• Average Base Pay: ₹12.2 LPA
  
• Source: Glassdoor
  

New Delhi

• Salary Range: ₹6.0 – ₹15.0 LPA
  
• Average Base Pay: ₹10.0 LPA
  
• Source: Glassdoor
  

Hyderabad

• Salary Range: ₹7.0 – ₹ 19.8  LPA
  
• Average Base Pay: ₹12 LPA
  
• Source: Glassdoor
  

Pune

• Salary Range: ₹5.0 – ₹10.0 LPA
  
• Average Base Pay: ₹7.0 LPA
  
• Source: Glassdoor
  

Chennai

• Salary Range: ₹5.0 LPA – ₹12 LPA
  
• Average Base Pay: ₹8.0 LPA
  
• Source: Glassdoor
  

Ahmedabad

• Salary Range: ₹4.0 – ₹12.0 LPA 
• Average Base Pay: ₹5.0 LPA
  
• Source: Glassdoor

Kolkata

• Salary Range: ₹4.0 LPA – ₹16.0 LPA
  
• Average Pay: ₹8.8 LPA
  
• Source: AmbitionBox
  

Gurugram

• Salary Range: ₹6.0 LPA – ₹17.9 LPA
  
• Average Base Pay: ₹10.4 LPA
  
• Source: Glassdoor

Mumbai

• Salary Range: ₹2.0 LPA- 14.0 LPA
• Average Salary: ₹5.0 LPA
• Source: AmbitionBox

Salary Variations by Industry & Company Type

Where you work matters just as much as your role. Some industries and companies offer significantly higher pay for machine learning engineer roles in India:

Source: AmbitionBox

These trends suggest that, next to location and experience, the industry you choose greatly influences your earning potential. Specialized sectors like fintech, AI-driven healthcare, and product engineering tend to pay a premium for in-depth ML skills.

Skills for Higher Machine Learning Salary

• Master core tools & skills: The right skills, such as a strong grip on Python, TensorFlow, PyTorch, and SQL, are essential. These are baseline skills for most machine learning roles and are often listed as must-haves by recruiters.
  
• Specialize in high-growth areas: Skills in Natural Language Processing (NLP), computer vision, and MLOps can help you stand out and often lead to better-paying roles due to their niche demand.
  
• Develop soft skills: Employers value professionals who can think critically, communicate effectively, and collaborate across teams. These abilities play a key role during interviews and team-based projects.
  
• Gain domain expertise: Applying machine learning to sectors like finance, healthcare, or retail shows practical understanding. This kind of domain alignment can influence salary offers significantly.
  
• Build a well-rounded profile: Combining technical know-how with real-world application is what truly defines the skills for a higher machine learning salary.

Top Machine Learning Jobs & Career Growth Paths

• The field of machine learning opens doors to a variety of career paths, each offering its opportunities for specialization and growth. Some of the most common job titles include Machine Learning Engineer, NLP Engineer, MLOps Engineer, and AI Researcher. While these roles share a foundation in core machine learning principles, they vary in terms of focus areas, required skills, and salary expectations.
• For example, Entry-level ML Engineers start around ₹3–5 LPA, gaining exposure to core model development.
  
• Transitioning to an NLP Engineer or MLOps Engineer role can lift pay to ₹12–15 LPA, especially with deployment or model pipeline skills.
  
• AI Researchers, meanwhile,  often command higher packages, reaching ₹60 LPA or more when working on cutting-edge projects or leading specialized teams.

Tips to Boost Your Machine Learning Salary

• Earn recognized certifications: Courses like the AWS Certified Machine Learning – Specialty and TensorFlow Developer Certificate add credibility to your profile and are often valued by top tech employers.
  
• Build a strong portfolio: Showcase your skills through real-world projects, participate in Kaggle competitions, or contribute to open-source ML repositories. Practical application often speaks louder than resumes.
  
• Stay updated with new tools: Familiarity with emerging tools in MLOps, AutoML, and cloud deployment platforms can increase your chances of landing better-paying roles.
  
• Focus on domain expertise: Knowing a specific sector, like healthcare, finance, or e-commerce, can help you stand out in specialized ML roles and command higher pay.
  
• Explore internal or cross-border moves: If you’re already working in a tech team, explore internal transitions into machine learning roles. For those aiming globally, building a strong GitHub presence and securing remote-friendly certifications helps.
  

Learn Machine Learning the Right Way – With GUVI

If you’re looking to upskill and grow in this field, GUVI’s Artificial Intelligence & Machine Learning course offers live classes, expert mentorship, and placement assistance while being IIT-M Pravartak certified! It’s the right pick if you want to build a strong career and get hired in top AI & ML roles.

In case you prefer to learn at your own pace, you can start with GUVI’s self-paced machine learning Course, which is perfect for beginners looking to build a strong foundation.

Wrapping Up

Machine learning continues to be one of the most promising career paths, not just in India but globally. It is backed by demand as well as by the scale of global investment in AI technologies. According to Statista, the global market size in the Machine Learning segment of the AI industry is expected to grow by a massive $462.9 billion between 2025 and 2031, marking an increase of over 438%. This kind of growth means more roles, better pay, and stronger career stability for professionals entering the space now.

In India, the machine learning engineer salary reflects this rising demand. Whether you’re just starting or looking to move into more advanced roles, there’s clear momentum in the job market. With the right skills, certifications, and experience, machine learning offers not just a job, but a long-term, future-ready career.

Frequently Asked Questions