Computer Vision Engineer Salary in India: Career Path and Key Skills for 2025

Do you know that the latest trend of computer vision, Vision Transformers (ViTs), is being adopted in medical imaging and autonomous vehicles? It utilizes a self-attention mechanism to process images, which outperforms traditional CNNs. This signifies a major leap in accuracy for object detection and classification.

The average Computer Vision Engineer salary in India for a fresher ranges from ₹5 L to ₹8 L per year. With 7 years of experience, you could also earn between ₹13 L and ₹15.8 L annually! 

Computer Vision Engineers are in growing demand thanks to their role in breakthroughs like autonomous vehicles and smart devices. As  AI and Machine Learning continue to evolve, so does the need for talent in this space. 

In this blog, you'll get a clear look at what shapes the Computer Vision Engineer salary in India, from career growth and must-have skills to what 2025 has in store.

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Computer Vision Engineer Salary in 2025: Insights and Trends

CV engineers receive one of the highest entry-level salaries, ranging from ₹60k to ₹80k per month. But why are CV engineers in such demand? Sectors like manufacturing, healthcare, and autonomous vehicles are widely adopting CV to enhance automation, accuracy, and real-time decision-making capabilities. 

As a result, India's computer vision market is projected to grow at a 22% CAGR from 2025 to 2031. 

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• Executive Diploma in Machine Learning and AI with IIIT-B
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These are also the high-paying industries for CV engineers. These industries rely on computer vision for tasks like disease diagnosis and self-driving car development..

Example: Self-driving cars utilize computer vision to navigate roads, identify objects, and respond to traffic signals. 

The rising demand for skilled professionals is pushing up salaries across these sectors. Let’s look at some of the factors leading to higher salaries for CV engineers:

• Business Impact: Computer vision enhances productivity, reduces costs, and improves customer experience, giving businesses a competitive advantage.
• Talent Scarcity: Limited skilled professionals drive high demand, with companies offering premium salaries to secure top talent.
• Field Complexity: Computer vision requires expertise in mathematics, programming, and machine learning, making it a highly valuable and sought-after skill.

Now, let’s look at the average computer vision engineer salary in India according to specific roles.

Computer Vision Engineer Salary in India: Role-Specific Breakdown

There are various job titles within the field of computer vision, such as Computer Vision Engineer, Machine Learning Engineer, Research Engineer, and Software Developer. The salary differences stem from the varying responsibilities and expertise required for each role. 

For instance, a Computer Vision Research Engineer often focuses on pioneering new algorithms. This requires a strong research background, which is reflected in the higher salary. On the other hand, a Machine Learning Engineer might focus on model development and deployment.

The table below shows average computer vision engineers salary in India, categorized by job title and role.

Source: Indeed, Glassdoor

As the complexity of the job increases, so does the compensation, which is reflected in the salary range for these positions. Now, let’s examine the average computer vision engineer in India, categorized by experience.

Computer Vision Engineer Salary in India: Freshers vs. Experienced

As you gain experience, your Computer Vision Engineer salary in India increases significantly. Senior engineers will work on complex tasks, including designing intricate systems, leading teams. Also, they have to make strategic decisions on projects. Hence, they are offered a higher salary. While freshers focus on learning and applying basic concepts. 

For instance, a fresher may be assisting with basic image processing tasks. But a senior engineer working on AI for autonomous vehicles must ensure vision algorithms meet strict real-time requirements. This requires deep expertise and justifies a higher salary.

The table below shows the average computer vision engineer salary in India, based on their experience:

Source: Glassdoor

Other than job titles and experience, another factor that determines your salary scale is the industry you are working in. Let’s look at the difference in computer vision engineer salaries in each industry.

Computer Vision Engineer Salary in India: Industry Insights

The salary differences across industries for Computer Vision Engineers in India stem from the varying complexities and impact of their roles in each sector. For instance, the automobile industry relies on CV for developing advanced driver-assistance systems (ADAS) and autonomous driving, precision and reliability are critical here. 

On the other hand, healthcare-focused roles typically involve less complexity in visual processing, such as medical imaging. Resulting in comparatively lower salaries. 

The table below shows the average computer vision engineer salary in India across different industries:

Source: AmbitionBox

The scope of responsibility and technological demand in each industry significantly influence salary levels. Now, let’s understand how computer vision engineer salaries vary according to the companies you choose. 

Computer Vision Engineer Salary in India: By Recruiters

The average computer vision engineer salary varies across different recruiters in India, reflecting the size, scope, and technological requirements of each company. The scale and complexity of their AI-driven projects also affects the salary range.

For instance, Qualcomm invests heavily in advanced mobile vision technologies, which require specialized expertise and offer higher compensation. Sony is involved in applications such as image processing in consumer electronics. As a result, they offer relatively lower pay.

The table below shows how the average computer vision engineer salary in India varies according to different recruiters:

Source: AmbitionBox

The average computer vision engineer salary in India can vary according to the company, industry,, and project complexity. However, your salary can also depend on the location you choose. Let’s understand more about this.

Also Read: Machine Learning Engineer Salary in India in 2025.

Computer Vision Engineer Salary in India: Differences by Location

Salary differences for Computer Vision Engineers across locations in India are driven by factors like demand, cost of living, and the presence of tech hubs. Cities such as Bangalore and Chennai, with their booming tech sectors and strong demand for talented engineers, typically offer higher salary packages.

For instance, a company in Bangalore working on AI technologies for autonomous vehicles may offer a higher salary compared to a similar role in Hyderabad.

The table below shows how the average computer vision engineer salary in India varies according to different locations:

Source: Glasdoor, Indeed

Now, we have seen how different factors affect a computer vision engineer's salary. But how can you maximize your earnings in your location or within your company? Let’s find out!

Smart Ways to Earn More as a Computer Vision Engineer

Computer vision is a comparatively new but highly competitive field. The field is mainly concentrated on innovation. Continuous learning and adaptation is necessary for working in this field. As the demand for skilled engineers grows, here are few ways to enhance your earning potential. 

Here are some smart tips to boost your salary as a Computer Vision Engineer:

• Continuous Learning and Hands-On Experience: Stay updated with the latest tools and technologies in CV such as TensorFlow, OpenCV, and PyTorch. You can attend online courses on platforms like upGrad for upskilling. Participate in webinars and join industry conferences. 
  • Gain practical experience by working on real-world projects, including internships, freelance opportunities, or personal projects. Platforms like GitHub and Kaggle also provide excellent opportunities for collaboration on open-source projects.

• Build a strong portfolio: Showcase your work by creating a portfolio that includes projects such as object detection, facial recognition, or autonomous vehicle simulations. 
  • For example, accomplishments such as publishing a paper, contributing to an open-source project, or solving real-world problems using computer vision will make you stand out.
• Expand your knowledge: Gain expertise in machine learning, AI, and deep learning. Tools like Keras and Scikit-learn are valuable in enhancing your skill set. Enhance your knowledge of algorithms and implement them in solving advanced computer vision challenges.
  • Keras provides easy-to-use APIs for rapid model development and experimentation. Scikit-learn offers powerful tools for data preprocessing, feature extraction, and model evaluation, all essential for computer vision tasks.
• Network: Engage with professional groups and attend meetups or industry-specific events like CVPR (Computer Vision and Pattern Recognition) and NeurIPS (Conference on Neural Information Processing Systems). 
  • You can also participate in specialized workshops, connect with industry experts, collaborate on projects, and stay informed about the latest trends in computer vision. 
• Specialize in high-demand areas: Focus on specialized fields within computer vision, such as medical image analysis, autonomous systems, or AI-driven video analytics. Specializing in a high-demand niche can significantly increase your earning potential.
  • Explore emerging areas like AI-driven diagnostic tools for early disease detection. Autonomous driving systems (ADAS), such as lane detection systems and object tracking for autonomous vehicles, are also key areas that help you stay ahead of market trends.        

Also Read: Top 12+ Best Courses in Artificial Intelligence To Enhance Your Skills for Career Growth in 2025

Now, let’s look into the key potential skills you need to focus on for a successful career as a computer vision engineer.

Key Skills That Set Successful Computer Vision Engineers

Becoming a successful Computer Vision Engineer is no easy feat, as it requires mastering a blend of complex technical skills. The application of computer vision are growing in every industry including automotive, telecom, retail, semiconductor, etc. From automating PCB (Printed Circuit Board) inspections to advancing robotic automation, engineers in this field are driving critical innovations.

Here are some key skills required to become a computer vision engineer:

• Programming and Software Development: Strong proficiency in programming languages such as Python, C++, and Java is essential. Python, in particular, is widely used for computer vision tasks, and knowledge of frameworks like OpenCV and TensorFlow is crucial for developing solutions efficiently.
• Machine Learning and Deep Learning: Understanding machine learning algorithms, neural networks, and deep learning frameworks like Keras and PyTorch is fundamental. This enables engineers to develop and train models for tasks like identifying objects, segmenting images, and recognizing faces.
• Image and Signal Processing: Skills in processing images and signals using techniques like edge detection, feature extraction, and noise reduction are vital. These techniques form the backbone of many computer vision applications, enabling better interpretation and analysis of visual data.
• Mathematics and Linear Algebra: A strong grasp of mathematics, particularly linear algebra, is essential for understanding and implementing CV algorithms. Concepts such as matrix manipulation and eigenvalues are key when working with transformations, optimization, and machine learning models.
• Computer Vision Algorithms and Techniques: Knowledge of algorithms such as SIFT, SURF, and RANSAC, as well as techniques like feature matching, optical flow, and object tracking, is necessary to solve real-world computer vision challenges effectively.
• Cloud Computing and Deployment: Familiarity with cloud platforms like AWS, Azure, or Google Cloud is beneficial, especially when deploying computer vision models at scale. Knowing how to use cloud-based tools for data storage, model training, and inference is crucial for large-scale applications.
• Version Control and Collaboration Tools: Proficiency in using version control systems such as, Git is necessary for collaboration and maintaining code quality in teams. It ensures smooth project management and efficient handling of code updates.

Top Soft Skills Required for a Computer Vision Engineer

While technical expertise is essential for a Computer Vision Engineer, soft skills are equally important for success in this field. Here are a few key soft skills for Computer Vision Engineers:

• Communication: The skill to convey complex technical ideas in a clear and understandable way to both technical and non-technical audiences.

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• Teamwork: Collaborating effectively with cross-functional teams, including data scientists, software engineers, and project managers.
• Problem-solving: Tackling challenges with a blend of creativity and analysis to devise effective and innovative solutions.

• Adaptability: Willingness to learn and understand new technologies and methods as the field of computer vision continues to evolve.
• Time Management: Prioritizing tasks efficiently and meeting deadlines in a fast-paced, dynamic environment.
• Critical Thinking: Evaluating problems from multiple perspectives and making data-driven decisions.

Success as a Computer Vision Engineer requires a solid blend of technical knowledge and essential soft skills. Let’s explore how upGrad can help you build the skills needed for success in this field.

Build a Long-Term Career in QA Computer Vision with upGrad

Qualcomm offers ₹18 - ₹35 Lakhs salary for a Computer Vision Engineer! However, to reach this level, you need a strong knowledge and technical skill set in AI, Machine Learning, Deep Learning, and Data Science. upGrad can help you bridge that gap with its specialized courses, developed in collaboration with top universities worldwide. 

These courses can help you upskill and reach your career potential. With over 10 million learners, 200+ programs, and 1,400+ hiring partners, upGrad offers flexible learning options that cater to students and working professionals. 

Apart from the courses mentioned above, here are some more upGrad courses that help you acquire expertise in AI & ML yourself: 

• Executive Programme in Generative AI for Leaders
• Job-ready Program in Artificial Intelligence & Machine Learning

Looking for a big leap in your career but not sure where to begin? Connect with top counselors at upGrad for personalized guidance and tailored advice. You can also visit upGrad’s offline centers for expert mentorship, hands-on workshops, and networking opportunities with industry leaders to fast-track your career growth.

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