Machine Learning Engineer Salary in Hyderabad is ₹11 LPA (2025)

We analyzed over 7,100 Machine Learning Engineer job listings and public data sources in Hyderabad. This thorough study has brought to light some key insights about the current scope of Machine Learning Engineer positions.

To give you a clearer picture of Machine Learning Engineer salaries in Hyderabad, India, we’ve highlighted several important points, such as:

• How much does a Machine Learning Engineer typically earn in Hyderabad?
• What are the most in-demand skills based on job requirements?
• How do experience and education levels impact annual compensation?
• Which industries have the highest demand for Machine Learning Engineers?

Let’s explore the answers from our detailed research on Machine Learning Engineer salary trends in Hyderabad.

💡 NOTE: Become a job-ready machine learning engineer with Codegnan’s following courses (include live coding tests and practical projects):

• Machine learning course in Hyderabad (1 month)
• Machine learning course in Vijayawada (1 month)

Key statistics at a glance:

• The average salary for a Machine Learning Engineer in Hyderabad is ₹11 Lakh.
• The top-paying companies for Machine Learning Engineers are Google, Qualcomm, Samsung, Phenom, and Jio.
• The most in-demand skills for Machine Learning Engineer jobs include Machine Learning, Python, Deep Learning, Artificial Intelligence, SQL, and Machine Learning.
• About 60% of Machine Learning Engineer jobs in Hyderabad offer salaries between ₹6-10 lakh.
• The IT sector accounts for almost 63.5% of the Machine Learning Engineer jobs available in Hyderabad.

What is the salary of a Machine Learning Engineer in Hyderabad?

The average salary for a Machine Learning Engineer in Hyderabad is ₹11 LPA (Lakhs Per Annum), based on data from 7.1k records on AmbitionBox.

With 1-2 years of experience, you can expect to earn around ₹7.7 LPA, which is a good starting point for this technical field.

For those with 5-6 years of experience, the average salary increases significantly to ₹14.5 LPA, showing the potential for higher earnings as you gain more experience.

This steady salary growth, nearly doubling within 5-6 years, highlights excellent career progression. The consistent rise in salary with each year of experience suggests that Machine Learning is a promising career in Hyderabad, offering long-term financial stability.

What are the different types of Machine Learning Engineers?

The data from Ambition Box highlights several important roles in the Machine Learning Engineers domain:

Senior Machine Learning Engineers and Lead Machine Learning Engineers are among the highest earners, making approximately ₹20 lakh and ₹25.5 lakh per year. 

Machine learning engineers hold mid-level positions, with salaries of around ₹11 lakh annually. Machine learning developers, who focus on developing and maintaining data infrastructure, earn about ₹5.7 lakh per year.

For those just starting out, Machine Learning Engineer Interns begin with an annual salary of ₹2.6 lakh, marking the initial step in the Machine Learning career pathway. 

This salary framework illustrates clear progress in the field, showcasing substantial earning potential as individuals gain experience and expertise.

Which companies pay the most to Machine Learning Engineers?

Based on the data from Ambition Box, here are some of the top-paying companies for Machine Learning Engineers along with their respective salaries based on experience:

Google offers the highest salaries across all experience levels. They pay ₹44.8 lakh for Machine Learning Engineers with 1 year of experience. This increases to ₹48.6 lakh for those with 2 years, ₹52.3 lakh for 3 years, 56.1 lakh for 4 years, and peaks at ₹59.8 lakh for engineers with 5 years of experience.

Qualcomm stands out as the second highest paying company for Machine Learning Engineers. They offer ₹21.5 lakh for those with 2 years of experience and ₹22.5 lakh for engineers with 3 years of experience.

In addition to Google and Qualcomm, other companies, including Jio, Samsung, Tiger Analytics, and Phenom, are also offering competitive salaries for Machine Learning Engineers.

This data clearly illustrates the trend of increasing salaries as professionals gain more experience in the Machine Learning domain.

Can Machine Learning Engineer jobs be done remotely?

Yes, Machine Learning Engineer jobs can be done remotely, but the options are quite limited.

We reviewed 2,596 job listings from Naukri and gathered some interesting insights a vast majority of jobs (92.12%) require working from the office, while hybrid arrangements account for about 6.39% of positions, with 180 jobs available. The number of remote positions is quite low, making up only 1.49% of total jobs, with 42 openings.

According to an analysis of job listings on LinkedIn, out of a total of 2,027 positions with specified work arrangements, 69.12% (1,401 jobs) are marked as work from office. Hybrid positions account for 19.54% (396 jobs), while remote opportunities make up 11.34% (230 jobs) of the total listings.

This data highlights the preference for on-site work among companies, with remote opportunities being more prevalent on LinkedIn compared to Naukri for Machine Learning Engineers

61% Machine Learning Engineer jobs in Hyderabad offer an average salary of 6-10 lakh

We analyzed 2,818 Machine Learning Engineer jobs in Hyderabad to gain insights into salary distribution.

The top salary segment for Machine Learning Engineers is in the ₹6-10 lakh range, with 1,716 jobs representing 60.89% of the total positions.

Following closely, the ₹10-15 lakh salary segment contains 1,516 jobs, accounting for 53.80% of the market, which suggests that there are abundant opportunities for more experienced professionals.

Additionally, the ₹3-6 lakh range includes 918 jobs, making up 32.58% of the total positions, addressing entry-level Machine Learning Engineers.

The analysis shows that the Machine Learning Engineer job market in Hyderabad offers competitive salaries, with a particular concentration in the mid-range salary brackets.

This suggests a healthy demand for professionals with a few years of experience, while also providing opportunities for both entry-level and highly experienced Machine Learning Engineers.

How many years of experience do you need to become a Machine Learning Engineer?

Based on the analysis of 241 Machine Learning Engineer jobs, the outcome reveals almost 70% of these positions require between 3 to 6 years of experience  

The top percentage category is for Machine Learning Engineers with 5 years of experience, accounting for 165 jobs representing 68.46% of the total positions. This is followed closely by those with 4 years of experience at 154 jobs (63.90%) and 3 years at 121 jobs (50.21%).

Interestingly, there’s a significant demand for mid-level professionals, with 6 years of experience accounting for 135 jobs (56.02%) and 7 years for 98 jobs (40.66%).

In contrast, the minimum percentage is represented by fresher positions, making up just 1.66% of the total jobs with 4 openings. Entry-level positions for those with 1 year of experience account for 8.71% (21 jobs).

There’s also a considerable demand for more experienced professionals, with 8 to 10 years of experience collectively representing 157 jobs (65.14% combined). Additionally, there are 25 positions (10.37%) available for those with 10+ years of experience.

This data suggests that while the majority of opportunities are for Machine Learning Engineers with 3 to 7 years of experience, there’s a spread of positions across various experience levels. Aspiring Machine Learning Engineers should focus on gaining relevant experience to improve their employability, with the sweet spot appearing to be around 4 to 6 years.

However, there are still opportunities for both entry-level candidates and highly experienced professionals in this competitive job market.

What skills are needed to be a Machine Learning Engineer?

Based on the analysis of 25,997 Machine Learning Engineer jobs, here are the top required skills lined up:

1. Machine Learning: Techniques and algorithms enabling computers to learn from and make predictions or decisions based on data. It’s crucial for the job as it forms the core of a Machine Learning Engineer’s work, allowing them to develop systems that can automatically improve through experience.
2. Python: Versatile programming language widely used in Machine Learning for its simplicity and powerful libraries like NumPy, Pandas, and Scikit-learn. It’s essential for Machine Learning Engineers as it’s the primary language for implementing ML algorithms and data manipulation.
3. Deep Learning: Subset of machine learning based on artificial neural networks, capable of learning from large amounts of unstructured data. It’s important for tackling complex problems like image and speech recognition, making it a valuable skill for advanced machine learning projects.
4. Artificial Intelligence: Development of computer systems able to perform tasks that typically require human intelligence, such as visual perception and decision-making. It’s crucial as ML is a subset of AI, and understanding the broader field helps in developing more sophisticated systems.
5. SQL: Structured Query Language for managing and querying relational databases. It’s essential for data extraction and manipulation, allowing Machine Learning Engineers to efficiently work with large datasets stored in databases.
6. Machine Learning: Interdisciplinary field using scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data. It’s important as it provides the foundational skills for working with and understanding data, which is crucial in machine learning.
7. Computer Vision: Field of AI that trains computers to interpret and understand the visual world. It’s valuable for jobs involving image-based machine learning tasks, such as object detection or facial recognition.
8. NLP (Natural Language Processing): A branch of AI dealing with the interaction between computers and humans using natural language. It’s important for jobs involving text analysis, chatbots, or any system that needs to understand or generate human language.
9. AWS (Amazon Web Services): Cloud computing platform offering a wide range of services for building and deploying machine learning models at scale. It’s crucial for jobs that require working with big data or deploying models in production environments.
10. Data Structures: Fundamental concept in computer science for organizing and storing data efficiently. It’s important for implementing efficient algorithms and optimizing machine learning models.
11. Computer Science: The study of computation, information processing, and the design of computer systems. It provides the theoretical foundation for machine learning, making it essential for understanding and developing ML algorithms.
12. Analytical Skills: The ability to collect, analyze, and interpret large amounts of data to solve complex problems. It’s crucial for deriving insights from data and making informed decisions in ML projects.
13. C++: High-performance programming language often used in machine learning for implementing computationally intensive algorithms. It’s important for jobs that require optimizing performance-critical parts of ML systems.
14. Monitoring: The practice of observing and tracking the performance of machine learning models and systems. It’s crucial for ensuring the continued effectiveness of deployed models and identifying areas for improvement.

What are the qualifications for a Machine Learning Engineer?

An interesting observation regarding the educational qualifications for Machine Learning Engineers comes from the analysis of 2,822 job listings.

A significant majority of the positions, accounting for 63.61% (1,795 out of 2,822), are available for candidates holding a bachelor’s degree, typically in areas like computer science, statistics, or other related quantitative fields. 

Also, 34.94% (986 out of 2,822) of the jobs prefer or require candidates to possess a postgraduate degree, such as a master’s or Ph.D. On the other hand, a mere 1.45% (41 out of 2,822) of positions cater to individuals with undergraduate qualifications, highlighting the limited opportunities for those without a full degree.

This data indicates that a bachelor’s degree is the minimum educational qualification for more than half of the Machine Learning roles, and the high percentage of postgraduate requirements points to a strong demand for advanced education and specialization in the Machine Learning domain.

👉 Find the complete machine learning syllabus

What industry has the most Machine Learning Engineers?

The sector with the highest requirement for Machine Learning Engineers is IT Services, making up 63.54% of the total job postings from a sample size of 2,822 positions on Naukri. This translates to 1,793 job opportunities, showcasing the strong presence of the IT Services industry in the Machine Learning Engineer job market.

The Technology sector ranks second, contributing 8.26% of the job listings, which amounts to 233 roles available. Following this, the Banking, Financial Services, and Insurance (BFSI) sector accounts for 4.93% of the total, with 139 positions, emphasising the vital role of Machine Learning in functions like financial analysis and risk management.

Additionally, Professional Services offer 5.49% of the opportunities, equating to 155 roles, while the Healthcare sector provides 5.71% of job postings with 161 positions. This rise in the healthcare domain highlights the growing reliance on data-driven approaches in medical practices and patient management.

Other sectors such as Media, Entertainment & Telecom (3.61%, 102 jobs), BPM (1.84%, 52 jobs), Education (1.70%, 48 jobs), Consumer, Retail, and Hospitality (2.13%, 60 jobs), Infrastructure, Transport & Real Estate (1.49%, 42 jobs), and Manufacturing & Production (0.89%, 25 jobs) also provide noteworthy opportunities, although in smaller numbers.

Overall, this data reveals the diverse demand for Machine Learning Engineers across various industries, underscoring the growing importance of Machine Learning skills in today’s workforce.

Data Sources

We hope you found some new and interesting insights. We have tried our best to bring you accurate data from credible resources. 

Key data sources for this research are:

• Ambition Box
• Naukri
• LinkedIn

Why Join Codegnan’s Machine Learning Course in Hyderabad

There is significant competition in the Machine Learning field, but with the right skills and guidance, you can secure a high-paying job.

With Codegnan’s Machine Learning Course training in Hyderabad, you’ll be well-equipped to join the top Java developers in 2024. 

Codegnan is a highly-rated (4.8/5, based on 2203 reviews) training institute in Hyderabad, offering comprehensive courses along with placement assistance to help you kickstart your career in Machine Learning.

Why choose Codegnan Machine Learning training in Hyderabad

• Expert-led instruction from industry professionals
• Hands-on experience with real-world projects
• Flexible learning options (online or offline)
• 24/7 student support
• Job placement assistance
• Industry-recognized certification
• Trained over 30,000 students worldwide with a proven track record of success (4.8/5 rating from 2180+ students)
• Lifetime access to learning materials and updates

Contact Codegnan Hyderabad:

• Name: Codegnan Hyderabad – Python, Java, Data Science, Machine learning, React JS training institute
• Phone: +91 89775 44092
• Email: info@codegnan.com 
• Hyderabad Address: Kothwal Madhava Reddy Plaza, Beside Indian Oil Petrol Bunk, JNTUH Metro Station, Nizampet X Roads, Hyderabad, 500072 
• Contact us: https://codegnan.com/contact-us/