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Wondering what is the range of Machine Learning Salary in India?
In a report titled “The Best Jobs in the US: 2019”, Indeed maintains that the job of a Machine Learning Engineer has grown to be a highly promising position – it records a growth of 344% and an average salary base of US$ 146,085. Machine Learning engineer salary in India may majorly depend upon multiple factors such as the company, location, skillset, and also the years of experience.
As you can see, 9 out of the 25 listed jobs on Indeed’s report are from tech-related fields. This is not surprising as tech-roles, particularly the ones in Data Science, AI, and ML, are gaining importance across various parallels of the industry. Because of this reason, companies are not shying away from offering increased Machine Learning salary in India.
Thus, if you have the required skillset and are ready to keep yourself updated, your career as a Machine Learning Engineer is expected to keep growing onwards and upwards. This line stands true especially when we consider that a Machine Learning Salary in India is directly or indirectly dependent on how upskilled and updated they are.
A recent report from Gartner states that by 2024, the rapid growth in AI will give rise to nearly 2.3 million job postings in Machine Learning.
We are sure, this must-have sparked a will to become a Machine Learning Engineer within you! Let’s take a look at who exactly is a Machine Learning Engineer and what is a typical Machine Learning salary in India?
What is Machine Learning?
According to SAS, “Machine learning is a method of data analysis that automates analytical model building. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention.”
Even though the term machine learning has been under the spotlight only recently, the concept of machine learning has existed since a long time, the earliest example of it being Alan Turing’s Enigma machine that he developed during World War II. Today, machine learning is almost everywhere around us, right from the ordinary things in our lives to the more complicated calculations involving Big Data. For instance, Google’s self-driving car and the personalized recommendations on sites such as Netflix, Amazon, and Spotify, are all outcomes of Machine Learning. Because of the demand, machine learning salary in India is one of the highest.
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Why Is Machine Learning Important In Today’s World?
After what is machine learning, comes the next important question – “what is the importance of machine learning?”
The main focus of machine learning is to help organizations enhance their overall functioning, productivity, and decision-making process by delving into the vast amounts of data reserves. As machines begin to learn through algorithms, it will help businesses to unravel such patterns within the data that can help them make better decisions without the need for human intervention. Apart from this upfront benefit, machine learning has the following advantages:
1. Timely Analysis And Assessment
By sifting through massive amounts of data such as customer feedback and interaction, ML algorithms can help you conduct timely analysis and assessment of your organizational strategies. When you create a business model by browsing through multiple sources of data, you get a chance to see the relevant variables.
2. Real-time Predictions Made Possible Through Fast Processing
One of the most impressive features of ML algorithms is that they are super fast, as a result of which data processing from multiple sources takes place rapidly. This, in turn, helps in making real-time predictions that can be very beneficial for businesses. For instance,
- Churn analysis – It involves identifying those customer segments that are likely to leave your brand.
- Customer leads and conversion – ML algorithms provide insights into the buying and spending patterns of various customer segments, thereby allowing businesses to devise strategies that can minimize losses and fortify profits.
- Customer retention – ML algorithms can help identify the backlogs in your customer acquisition policies and marketing campaigns. With such insights, you can adjust your business strategies and improve the overall customer experience to retain your customer base.
3. Transforming Industries
Machine learning has already started to transform industries with its ability to provide valuable insights in real-time. Finance and insurance companies are leveraging ML technologies to identify meaningful patterns within large data sets, to prevent fraud, and to provide customized financial plans for various customer segments. In healthcare, wearables and fitness sensors powered by ML technology are allowing individuals to take charge of their health, consequently minimizing the pressure on health professionals. So, there are opportunities galore for machine learning engieers, and the indispensable nature of their jobs ensures that machine learning salary in India is quite elevated.
Reasons to Become a Machine Learning Engineer
The lucrative nature of the machine learning engineer salary or ml engineer salary in India attracts a lot of professionals to this field. But if you need more reasons to pursue the role of a machine learning engineer, here are some to convince you:
Exciting Opportunities
As a branch of the artificial intelligence field, machine learning enables computer systems to continuously enhance their capabilities in various tasks by utilizing data and statistical methods. Instead of manually programming a computer to improve, machine learning creates an environment for the computer to optimize its own performance through computational statistics, data modeling, and mathematical techniques because of which they take attractive salary of machine learning engineer in India. This dynamic field presents thrilling and demanding opportunities across a range of industries and applications.
Real-Time Application of Math
If you have a love for math and a drive to implement complex equations and theories into practical solutions, a career as a machine learning engineer may be the perfect fit for you. You get to exercise your skills in linear algebra, calculus, probability, and statistics on a daily basis during every step of your machine learning career.
Innovative Computer Programming Paths
Since the field of machine learning revolves around computers and their optimization, being proficient in computer programming is a crucial asset. A career in machine learning engineering will enable you to utilize advanced languages like Python in state-of-the-art projects. Furthermore, you’ll have the chance to deepen your knowledge of machine learning algorithms, structures, modeling by taking attractive machine learning expert salary in India.
Continuous Learning
As a field still in its early stages, machine learning offers countless unexplored solutions, algorithms, and applications. The possibilities for innovation in healthcare, marketing, online security, and smart cars are endless. As a machine learning engineer, you could play a key role in revolutionizing these industries.
With its focus on problem-solving and adapting technology to specific needs, machine learning offers endless opportunities and attractive ml engineer salary in India to continually learn and advance through active participation in industry events. Your career in machine learning is sure to be a fulfilling journey filled with exciting discoveries and boundless growth.
What does a Machine Learning Engineer do?
The job of a Machine Learning Engineer is quite similar to that of a Data Scientist, in the sense that both roles involve working with vast volumes of data. Hence, both Machine Learning Engineers and Data Scientists must possess excellent data management skills. However, that’s all the similarity that these two roles share.
Data Scientists are mainly concerned with generating valuable insights for driving business growth through data-oriented decision making. In contrast, Machine Learning Engineers focus on designing self-running software for predictive model automation.
Usually, Machine Learning Engineers work in close collaboration with Data Scientists. While Data Scientists extract meaningful insights from large datasets and communicate the information to business stakeholders, Machine Learning Engineers ensure that the models used by Data Scientists can ingest vast amounts of real-time data for generating more accurate results.
Responsibilities of a Machine Learning Engineer
- To study and convert data science prototypes.
- To design and develop Machine Learning systems and schemes.
- To perform statistical analysis and fine-tune models using test results.
- To find available datasets online for training purposes.
- To train and re-train ML systems and models as and when necessary.
- To extend and enrich existing ML frameworks and libraries.
- To develop Machine Learning apps according to customer/client requirements.
- To research, experiment with, and implement suitable ML algorithms and tools.
- To analyze the problem-solving capabilities and use-cases of ML algorithms and rank them by their success probability.
- To explore and visualize data for better understanding and identify differences in data distribution that could impact model performance when deploying it in real-world scenarios.
An Overview of the Key Tasks Performed By a Machine Learning Engineer
Seeking machine learning engineer salary for freshers. Before learning about the machine learning expert salary in India or ML salary in India, you should become aware of your key responsibilities:
- Data Collection and Preprocessing: Machine learning engineers will have to work together with data scientists to acquire and clean data. These professionals look after everything from data extraction and transformation to cleaning. It ensures that the data becomes fit for training machine learning models.
- Model Development: Creating machine learning models is at the core of your job responsibility. As a machine learning engineer, you will have to figure out the most appropriate algorithm for your models. Moreover, you will have to adjust the model parameters and track their performance for accurate classification or prediction.
- Feature Engineering: Machine learning engineers are responsible for creating variables or features to enhance the capabilities of a model. It ensures that the model becomes more efficient and accurate at finding patterns from data.
- Model Training: Machine learning engineers make use of labeled data to train models. By exposing the models to real-world examples, machine learning engineers can achieve satisfactory results.
- Model Deployment: Machine learning engineers must deploy them within the production environment after training models. It helps in making them accessible to end-users and facilitates smooth integration with software applications.
- Supervision and Upkeep: Machine learning models need to be constantly monitored so that they can perform according to real-world scenarios. Machine learning engineers perform this supervision to identify and fix issues as soon as they arise.
Skills Needed to Learn Machine Learning
Now that you know why you should choose a career in machine learning and have perhaps made a decision as well, let us tell you a few important skills that you need to have to make the most of this opportunity.
To make your career to grow as a machine learning engineer and earn the highest possible machine learning salary in India, you need to have update yourself with:
- Statistics and probability: Your understanding of algorithms has a lot to do with your knowledge of theories. Hidden Markov models, Naïve Bayes, and Gaussian Mixture, amongst other models, are great examples. If you aren’t good at statistics and probability, you will find these algorithms very difficult to understand.
- Data evaluation and modeling: An important part of ensuring the efficiency of the estimation process with ML is to evaluate the effectiveness of different models at regular intervals. You can use different methods, such as regression and classification, to measure the error or accuracy of a given model. You also need an evaluation strategy to go with it.
- ML algorithms: Knowing how different machine learning algorithms work and which algorithm fits in a particular situation is very important. You would need to develop an understanding of subjects like partial differential equations, gradient descent, quadratic programming, convex optimization, and others.
- Programming languages: For a career in machine learning, you also need to be skilled in different programming languages, such as Java, R, Python, and C++. These languages will help you at different stages of your machine learning project.
- Signal processing techniques: Feature extraction is very important to machine learning. You may have to work with several advanced signal processing algorithms, including bandlets, shearlets, contourlets, and curvelets, amongst others. Learn more about machine learning required skillsets.
Advanced Skills Required By Machine Learning Engineers
If you are waiting for a hike in your machine learning developer salary or machine learning salary in India, familiarize yourself with the following:
Neural Network Architectures
Neural networks are a powerful set of algorithms used in machine learning, offering a diverse range of models that play a crucial role in the field. For any machine learning enthusiast, having a strong grasp of neural networks is essential for several reasons. Firstly, neural networks provide valuable insights into the inner workings of the human brain, allowing for the creation and simulation of artificial versions. This fascinating parallel between natural and artificial intelligence is a key aspect of understanding the potential of neural networks.
Additionally, neural networks offer a deeper understanding of parallel and sequential computations. By exploring these computation methods, individuals can gain an understanding of the capabilities and shortcomings of neural networks in solving complex tasks.
Natural Language Processing
It’s imperative that we recognize the significance of natural language processing in the fields of artificial intelligence and machine learning. Some of the most notable libraries and techniques for natural language processing that are utilized in the world of machine learning include:
- Gensim and NLTK
- Word2vec
- Sentiment analysis
- Summarization
Audio and Video Processing
Unlike natural language processing, we have the ability to focus exclusively on audio signals when employing audio and video processing. To successfully accomplish this task, a machine learning engineer must possess knowledge of key concepts like Fourier transforms and TensorFlow.
Reinforcement Learning
Undoubtedly, reinforcement learning plays a vital role in understanding the intricacies of deep learning and artificial intelligence. For those who are new to the machine learning field, it is essential to understand the fundamental principles of reinforcement learning.
Distributed Computing
Being employed as an AI and machine learning salary or machine learning jobs salary entails handling vast amounts of data, spanning across various systems rather than just one isolated system. In order to excel in this role, possessing a strong understanding of concepts related to distributed computing is crucial.
Unix
Unix and Linux serve as the mainstay for machine learning engineers, with a majority of their work concentrated on these platforms. While there may be occasional use of Windows or Mac, a comprehensive understanding of Unix is essential for success in this field.
Apache Kafka
Mastering the intricacies of Apache Kafka, including its powerful elements like Kafka Streams and KSQL, is pivotal in the preprocessing stage of data for machine learning. From designing multi-cloud and hybrid cloud solutions to incorporating essential business information like latency and model accuracy, knowledge of Apache Kafka is vital for a successful machine learning engineer.
Weka Platform
Machine learning is a widely recognized non-linear process that requires multiple iterations. Recently, a platform called Weka or Waikato Environment for Knowledge Analysis has been developed specifically for applied machine learning. Its rising popularity solidifies its crucial position on the skillset of a machine learning engineer.
Rapid Prototyping
A machine learning engineer’s proficiency in choosing the right learning method or algorithm is a crucial indication of their excellent prototyping abilities. These skills are invaluable in the real world, as they can greatly impact the budget and timeline for completing a successful machine learning project.
Jupyter Notebook
By utilizing Jupyter, a powerful computational platform designed for Python-based data science, machine learning engineers can create compelling demonstrations of their process flow in a clear, step-by-step manner through the use of Jupyter Notebook by taking awesome machine learning salary.
Machine Learning Salary in India
The demand for Machine Learning is high but companies require individuals to have the correct skill sets. The demand for these engineers are always high. The list is endless. That’s the primary reason machine learning salary in India is quite high. The ever increasing demand. Additionally, the better the experience, the higher is the salary. The average machine learning salary in India, according to Payscale, is approximately Rs. 686,281 per year, inclusive of bonuses and profit-sharing.
Factors Affecting Machine Learning Salary in India
The four main factors affecting the Machine Learning Salary in India are:
- Company – The company that you work for will have a direct impact on the salary you get. In India, companies like PRISM, Catalyst Solutions, Vbeyond Corporation, Facebook, Google, Salesforce, Apple etc are some options where one can find job opportunities such as ML engineer salary in India with the highest machine learning engineer salary.
- Experience – The more experience you have, the better is the ability to understand the roadblocks and provide quick solutions for bugs. A combination of experience and company will get salaries and positions that help create a mark. Especially ML engineer salary in India is highly dependent upon their years of experience. An entry-level ML engineer salary is around 5.1 LPA, whereas a person with more than ten years of experience can earn more than 20 LPA,
- Location – In the coming years, location is all set to play a smaller role in the salary you can expect. But, even then, location will continue to have an impact on the salary you can ask for and get from a prospective employer. The location impacts the machine learning salary mostly due to the fact that not every city in India has the infrastructure required for a machine learning engineer
- Skill – The important skills you have, the better is the ability to understand. Location is all set to play a vital role in deciding the machine learning salary in India.
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Machine Learning Salary in India: Based On Company
It is an accepted fact, the bigger the brand or company, the higher is the salary an individual can expect. Let us look at some of the highest pay packages – Tata Consultancy Services Limited offers about Rs. 4,42,000 per annum as salary. It is followed by Intel Corporation at Rs 20,00,000.
Machine Learning Salary in India: Based on Experience
The more experience you have the higher your pay package will be. So, if you are a beginner and have only recently entered the industry, you will have to moderate your hopes accordingly. So, let us break down the machine learning salary in India, depending on how many years of experience you have in your bag –
Let’s see how a machine learning salary in India varies based on experience.
Entry-Level Machine Learning Salary in India
The average entry-level machine learning salary in India is ₹501,058.
Mid-Level Machine Learning Salary in India
The average mid-level machine learning salary in India is ₹1,142,459.
Experienced Machine Learning Salary in India
The average experienced machine Learning salary in India is ₹1,999,619.
Machine Learning Salary in India: Based on Location
Though Covid-19 may reduce the impact of location on salaries in the future, currently, location plays a crucial factor in determining machine learning salary in India. The Silicon Valley of India, Bangalore offers the highest salaries, with Machine learning in the city earning approximately 21% more than their counterparts in other cities. The comparison is done against the national average. Chennai, the other city competing for the Silicon Valley title, offers salaries that are 5% less than the national average.
Machine Learning Salary in India: Based on Skills
Let’s discuss how machine learning salary in India increases with skillset. As we mentioned earlier, you have to possess an impressive set of skills to acquire the best-paid jobs in the highly competitive market for machine learning engineers. Some skills get you a higher paycheque. So, try to invest in these skills.
- Machine Learning – ₹706,169
- Python – ₹612,684
- Deep Learning – ₹754,250
- Natural Language Processing(NLP) – ₹697,670
- Computer Vision- ₹736,976
Machine Learning and Deep Learning are sure to bring you more than the average machine learning salary in India. In terms of popularity response too, these two skills ranked the highest.
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Machine Learning Salary in Other Countries
Machine Learning salary in The US: $111,297.
Machine Learning salary in The UK: £50,296.
Machine Learning Job Roles
1. Machine Learning Engineer
Artificial Intelligence and Machine Learning are mere umbrella terms for a number of applications that are applied across disciplines and technologies. They also involve robotics, data analytics, web development, developing chatbots, intelligent application development, and much more.
Since late 2017, AI and ML have taken the nation by storm. Frameworks such as OpenCV, PyTorch, and TensorFlow have become buzzwords for today’s AI/ML enthusiasts.
Responsibilities of a Machine Learning Engineer
- To study and convert data science prototypes.
- To design and develop Machine Learning systems and schemes.
- To perform statistical analysis and fine-tune models using test results.
- To find available datasets online for training purposes.
- To train and re-train ML systems and models as and when necessary.
- To extend and enrich existing ML frameworks and libraries.
- To develop Machine Learning apps according to customer/client requirements.
- To research, experiment with, and implement suitable ML algorithms and tools.
- To analyze the problem-solving capabilities and use-cases of ML algorithms and rank them by their success probability.
Salary of a Machine Learning Engineer in India
The average annual salary of a machine learning engineer is ₹671,548. Machine learning engineers with less than 1-year experience earns around ₹500,000 per annum which is clearly one of the highest entry-level salaries in India. Early level machine learning engineers charge ₹672,106 per annum, obviously, depending on their skill set, location, and demand.
The average salary of a mid-level engineer is ₹1,173,074 per annum. If they think that’s great, you will find the salary of senior-level engineers (more than 10 years experience) inspiring as they earn more than 2 million rupees per annum. An ML engineer salary in India may vary according to the city or the experience the person may have.
2. Data Scientist
Data science is basically statistics implemented through programming. Alongside R, Python has also shown its mettle in sorting out data as per generic as well as specific requirements. As far as India is concerned, Python programmers for data science earn more than both software developers as well as DevOps programmers. The reason for this is that data collection, data cleaning and processing is becoming very common nowadays as companies need data to gather market and customer information.
This requires a niche of Python programmers who are specially trained in the collection and processing of data through libraries like NumPy and Pandas. Data scientists are in high demand in major metros like Delhi-NCR and Mumbai and emerging cities such as Pune and Bangalore.
Responsibilities of Data Scientists
- Gathering vast amounts of structured and unstructured data and converting them into actionable insights.
- Identifying the data-analytics solutions that hold the most significant potential to drive the growth of organisations.
- Using analytical techniques like text analytics, machine learning, and deep learning to analyse data, thereby unravelling hidden patterns and trends.
- Encouraging data-driven approach to solving complex business problems.
- Cleansing and validating data to optimise data accuracy and efficacy.
- Communicating all the productive observations and findings to the company stakeholders via data visualisation.
Data Scientists Salary Range in India
The average data scientist’s salary is ₹708,012. An entry-level data scientist can earn around ₹500,000 per annum with less than one year of experience. Early-level data scientists with 1 to 4 years of experience get around ₹610,811 per annum.
A mid-level data scientist with 5 to 9 years of experience earns ₹1,004,082 per annum in India. As your experience and skills grow, your earnings rise dramatically as senior-level data scientists around more than ₹1,700,000 a year in India!
3. Data Engineers
The primary job of a Data Engineer is to design and engineer a reliable infrastructure for transforming data into such formats as can be used by Data Scientists. Apart from building scalable pipelines to covert semi-structured and unstructured data into usable formats, Data Engineers must also identify meaningful trends in large datasets. Essentially, Data Engineers work to prepare and make raw data more useful for analytical or operational uses. There are many myths about data engineers and most of them are far from reality.
In an organization, the position of a Data Engineer is as vital as that of a Data Scientist. The only reason why Data Engineers remain away from the limelight is that they have no direct link to the end product of the analysis.
Responsibilities of Data Engineers
- Integrate, consolidate, and cleanse data collected from multiple sources.
- Prepare raw data for manipulation and predictive/prescriptive modeling by Data Scientists.
- Develop the necessary infrastructure for optimal extraction, transformation, and loading of data from disparate sources using SQL, AWS, and other Big Data technologies.
- Deploy sophisticated analytics programs, machine learning algorithms, and statistical techniques to build data pipelines.
- Assemble vast and complex data sets to cater to the functional and non-functional business requirements.
- Identify and develop innovative ways to improve data reliability, efficiency, and quality.
- Develop, construct, test, and maintain data architectures.
Skills required to be a Data Engineer
- Active project management and organizational skills.
- Strong analytic skills to handle and work with large, unstructured datasets.
- Strong programming flair in trending languages, including Python, Java, C++, Scala, Ruby, etc.
- Advanced working knowledge of SQL, along with experience in working with relational databases.
- Proficiency in working with a wide variety of databases.
Data Engineer Salary Range in India
According to Glassdoor, the average Data Engineer salary in India is Rs.8,56,643 LPA. But of course, the Data Engineer salary depends on several factors, including company size and reputation, geographical location, education qualifications, job position, and work experience. Reputed companies and big players in the Big Data industry like Amazon, Airbnb, Spotify, Netflix, IBM, Accenture, Deloitte, and Capgemini, to name a few, usually pay high compensation to Data Engineers. Also, the more your past work experience in Big Data, the higher will be your market value.
Despite the global demand-supply paradox (the demand for Data Engineers far exceeds their supply), the career prospect of Data Engineers looks promising in India. According to Analytics India Magazine report,
“While IT firms have shown a negative trend, the demand for data engineering professionals has increased across the companies, resulting in a significant jump in their salary structure. Whereas for salaries across analytics skills, advanced analytics roles and predictive modeling professionals grabbed the limelight compared to other roles.”
As for Data Engineers in their early career (1-4 years of experience), they make anywhere around Rs.7,37,257 LPA. As they proceed to mid-level (with 5-9 years of experience), the salary of a Data Engineer becomes Rs.1,218,983 LPA. Data Engineers having over 15 years of work experience can make more than Rs.1,579,282 LPA.
In-demand Machine Learning Skills
4. Data Analyst
Data Analysts are professionals who translate numbers, statistics, figures, into plain English for everyone to understand.
Given the circumstances, there’s always an increasing scope for Data Analysts at the workplace, and it may be an excellent choice for those who have a strong foothold in mathematics, statistics, computer science or business backgrounds. This position includes data mining, fluency in languages like SQL, Python, etc. to extract the relevant insights from the data sets as well as channeling those ideas through visualizations and reports.
Data Analyst Responsibilities
- To analyze and mine business data to identify correlations and discover valuable patterns from disparate data points.
- To work with customer-centric algorithm models and personalize them to fit individual customer requirements.
- To create and deploy custom models to uncover answers to business matters such as marketing strategies and their performance, customer taste, and preference patterns, etc.
- To map and trace data from multiple systems to solve specific business problems.
- To write SQL queries to extract data from the data warehouse and to identify the answers to complex business issues.
- To apply statistical analysis methods to conduct consumer data research and analytics.
Data Analyst Salary in India
For a data analyst in India, having 1 – 4 years of experience has a gross earning (including tips, bonus and overtime pay) of Rs 3,96,128, while a mid-career Data Analyst with 5 – 9 years of experience can make up to Rs 6,03,120 based on the organization and the location of the working place. And if you are a matured and experienced Data Analyst who has been in the industry or 10 – 19 years can earn an average total compensation of Rs 9,00,000.
Source: Payscale
– 78% of the analytics professionals in India are under the salary bracket of 0 – 6 Lakhs at their entry level, but since there has been a rise in the number of freshers in Data Analysis in India, this is an excellent indication for maturing the industry.
– The salaries for 4 – 6 years of experienced remain stable at 8.7 Lakhs.
– For the Senior Data Analyst having substantial experience of 12 or more years has witnessed a sharp 20% rise in their salaries last year.
5. Software Developer/Engineer (AI/ML)
Software Developers/Engineers with specialization in AI/ML are the creative minds behind intelligent computer programs. Their main job is to develop efficient ML algorithms and applications. Software Developers/Engineers design, develop, and install AI/ML software solutions; create specific computer functions; prepare product documentation, flowcharts, layouts, diagrams, charts, etc. for visualization; write and test code; create technical specifications, upgrade and maintain systems, and much more.
Skills required: Software Developers/Engineers (AI/ML) must be proficient in coding in multiple programming languages, including Python, Java, R, C, C++, Scala, etc. They must possess a good understanding of operating systems, data structures, data architecture, computer architecture, data analytics, distributed processing, software testing and debugging, among other things. Also, they must have extensive knowledge of ML concepts, algorithms, systems, and tools.
The Average AI Software Developer in India is Rs. 700,000 per annum
6. Human-Centered Machine Learning Designer
Machine Learning has an exclusive branch that is dedicated to designing ML algorithms centered around humans. Hence, the name Human-Centered Machine Learning. Human-Centered Machine Learning Designers are responsible for creating intelligent systems that can “learn” the preferences and behavior patterns of individual humans through information processing and pattern recognition.
These systems require minimal or no human intervention or even cumbersome programs to account for every conceivable user scenarios. Netflix and Amazon’s Recommendation Engine is an excellent example of Human-Centered Machine Learning.
Skills required: As is true of any Machine Learning career path, Human-Centered Machine Learning Designers must also possess an in-depth understanding of various ML concepts, algorithms, and how they function. They should also have a good base in Mathematics and Statistics along with coding proficiency.
Required Qualification:
- An advanced degree in Computer science-related fields.
- In-depth knowledge of data modeling and data architecture.
- Prior experience in Python, R, or Java.0
- Good grip on advanced maths such as linear algebra, group theorem, statistics, etc.
- Expertise in machine learning frameworks and distributed computing systems, like TensorFlow and Hadoop.
Recruiters for this job in India include Accenture, Cognizant, FactSet, etc.
7. NLP Scientist
Natural language processing (NLP) aims to impart machines with the ability to understand natural human languages. NLP Scientists are primarily responsible for designing and developing machines and applications that can learn the patterns of speech of a human language and also translate spoken words into other languages. The goal here is to help machines comprehend human languages as naturally as humans do. Grammarly and Duolingo are two excellent examples of NLP applications.
Skills required: Since the primary job of NLP Scientists is to teach machines how to understand the nuances of human languages, they must be fluent in the syntax, spelling, and grammar of at least one language (the more, the better). Also, they should have the basic-level ML skills.
Salary for NLP in India:
The average salary for skill in India: Rs. 919,108 per annum.
8. Director of Analytics
The Director of Analytics is responsible for supervising the Data Analytics and Data Warehousing departments. Besides, the Director of Analytics aligns the management, development, and integration of Data Analytics and Business Intelligence to support the mission and vision of the company.
Skills required:
- The ability to match the correct technical skill based on the business situation so that the data-driven business can improve its technical capabilities.
- Not only mitigating the prevailing business crisis but to predict the probable falls. Therefore, an eye for identifying opportunities for improvement.
- Hiring and structuring teams and maintaining a high level of job satisfaction amongst them.
- The ability to create an environment of learning.
- Maintaining discipline and encouraging innovation amongst the team members
- The ability to guide a business through a data journey.
Required Qualification:
- A master’s degree in data science, maths, computer science, or related fields
- A minimum of ten years of working experience in the related role
- Demonstrated expertise in business process analysis and data architecture designing.
Average Director of Analysis Salary in India is Rs. 3,719,375.
9. Principal Data Scientist
A Principal Data Scientist is tasked with the duty of supervising and managing the entire Data Science team. He / She guides them in the development process of analytics models and is also the leading voice behind developing project plans. Principal Data Scientists must possess strong statistical analysis skills along with a knack for solving complex problems.
Skills Required:
- Having in-depth knowledge of data science
- Knowledge of statistics
- Expertise in multiple programming languages
- The ability of critical thinking
- Leadership qualities to lead a team and support them
- Knowledge of other technical fields such as data manipulation and analysis, data visualization, machine learning, Big Data, deep learning, model deployment, etc.
- Both verbal and written communication skills
- Structured thinking.
Required Qualification:
- A Master’s/ Ph. D degree in Data Sciences/ Machine Learning/ Artificial Intelligence/ Computer Science/ Mathematics/ Statistics/ Engineering/ Finance/ Management/ Economics.
- A minimum of 8 to 10 years of working experience in tech-related fields such as Big Data, Data Architecture, Business Analytics applications, and Business Intelligence solutions.
Average Principal Data Scientist Salary in India is Rs. 3,719,375.
10. Computer Vision Engineer
Computer Vision Engineers apply computer vision research techniques on vast amounts of data to find solutions to various real-world problems. They work in close collaboration with other teams to develop and implement novel embedded architectures. Also, Computer Vision Engineers possess in-depth knowledge of ML systems.
Responsibilities of a Computer Vision Engineer:
- Development of computer vision model
- Prototyping algorithms and quantifying the results
- Scene construction
- Image Restoration
- Training data creation
- Collaborating and reviewing codes with domain experts
- Staying updated with the latest journals and research papers.
Skills required:
- Handling the development and analysis of machine learning applications for advanced projects
- Developing algorithms and software in the interior sensing space using programming languages.
- Leading the development of algorithm specifications such as FMEAs
- Understanding the sensor system interaction that does improvements by identifying required changes and improvements needed to meet the objectives.
- Developing and implementing signal processing and sensor fusion algorithms like real-time data processing.
Salary of Computer vision engineer in India:
The Average Salary of computer vision engineer in India is ₹512,820 per annum.
11. Algorithm Engineer
Algorithm Engineers design, analyze, implement, optimize, profile, and evaluate computer/ML algorithms. Their goal is to minimize the gap between algorithm theory and practical applications of algorithms in Software Engineering.
Responsibilities of an Algorithm Engineer:
- Creating algorithms for different AI applications that help recognize a pattern in data and draw conclusions from them.
- Overall testing of an algorithm to use in AI technology.
- Algorithm result testing to assess the degree of success of an algorithm.
- Reporting algorithm to keep track of present findings in a user-friendly manner.
- Research potential improvements in the algorithm so that the efficiency can be enhanced.
- Continuously communicating and collaborating with the team and fellow engineers and clients.
The average salary of an algorithm engineer salary in India:
12. Computer Scientist
The primary task of Computer Scientists is to develop new technologies, systems, and computer-based solutions. Their work revolves around various technologies, including AI, Robotics, Information Technology, and Virtual Reality. They work together in a team along with Computer Programmers, Information Technology Professionals, Mechanical/Electrical Engineers, etc.
Responsibilities of a computer scientist:
- Identifying and solving computational and maths-related problems
- Developing new products that solve practical problems
- Researching regarding various experiments and models
- Being a part of a research team with programmers, IT developers, and other engineers and creating new products
- Seeking improvements in the present computer system and software.
Skills Required:
- Proficiency in maths
- Excellent knowledge of computer and technology
- An eye for details and the ability to trace the problems to their core
- High accuracy and persistency
- Being highly organised to manage a large amount of data and information.
Salary of computer scientist in India:
Average computer scientist salary in India is Rs.1,892,000 per annum.
How to Become a Machine Learning Engineer?
The following steps can help you become one of the best machine learning engineers. With that, you can also land a credible job along with a great ML engineer salary in India.
Step 1: Level up your Python & Software skills
A high-level, easy-to-use language, Python is the language of choice for AI specialists, data scientists, and machine learning engineers.
Python’s syntax is easy to learn, and it has tonnes of already built-in libraries.
Another important thing to get super familiar with is Github.
Read some books or articles to get an idea of the tools you’ll need to run Python on datasets.
Step 2: Look into machine learning algorithms
After you are familiar & comfortable with Python, you can start looking at machine learning algorithms. Be sure to read up on the theory related to each algorithm so you can implement models with ease.
Step 3: Work on mini projects
Now that your initiation into the realms of Python and machine learning is complete (both individually and combinedly), it’s time to take all that knowledge and start implementing it in projects.
Step 4: Take things to the next level with Hadoop and Spark
Hadoop and Spark are the 2 systems you’ll want to tackle after you’ve built some proficiency in working with data sets using Python. These big data frameworks will enable you to work with data at the terabyte and petabyte scale.
Step 5: Move onto TensorFlow
Machine learning algorithms? Check. Big data frameworks? Check. Advanced machine learning? Start working with TensorFlow.
Step 6: Go Big
After working with all the building blocks, it’s time now to wrestle with big data sets and apply all the knowledge you’ve gained in the previous 5 steps.
Step 7: Keep on practising and growing
The final step is to simply practice and repeat the above mentioned 6 steps. You are now at a point where you can build your own machine learning models. It’s time to refine those skills now and keep getting better and earn a great job with a great machine learning engineer salary.
Why is the demand for Machine Learning Engineers increasing?
In the last decade, the demand for Machine Learning Engineers has even surpassed the need for Data Scientists. In the 2017 LinkedIn US Job report, Machine Learning Engineer took the top rank with a recorded growth of 9.8 times in five years (2012-17).
As for the global Machine Learning market, it is predicted to exceed $39,986.7 million by 2025, growing at a CAGR of 49.7% between 2017 and 2025. These stats make it clear that the ML market is expanding at an unprecedented pace. In light of the growing competition, companies will have to hire talented ML Engineers along with other Data Science professionals to stay grounded firmly in the market. Some talented engineers can land some of the best jobs where machine learning jobs salary would be great, and the experience would only make you a better professional with a higher position in the company.
What are The Advantages of a Machine Learning Course?
1. Better Career Opportunities and Growth
A report by TMR notes that MLaaS (Machine learning as a Service) is predicted to grow from to $19.9 billion by the end of 2025, from a mere $1.07 billion in 2016. This is a staggering amount of growth, both in absolute terms, as well as year-on-year.
Machine learning makes a mockery of anything that can be called “important” – both at a financial as well as a global scale. If you are looking to take your career to another level, Machine Learning can do that for you. If you are looking to involve yourself in something that will make you part of something that is global as well as contemporary relevance, Machine Learning can do that for you as well.
2. Better Salaries
The best machine learning engineers these days are paid as much as immensely popular sports personalities! And that’s no exaggeration! According to Glassdoor.co.in, the average machine learning engineer salary is 8 lakhs per annum – and that’s just at the starting of one’s career! An experienced machine learning engineer takes home anywhere between 15 to 23 lakhs per annum. An ML engineer salary depends on the kind of experience that a candidate has gained in different industries. The machine learning salary can vary according to different cities as well.
3. Lack of Machine Learning Skills is Plaguing Corporations
Given the rapid rate at which technological leaps have been made, a lot of corporations have been left playing catch up. Digital transformation is a huge industry, and the truth of the matter is that there are simply not enough machine learning professional to cater to new industry demands.
4. Machine learning and Data Science are intricately linked
If religion ruled the masses for entire centuries before modernity, it is now true that Data Science rules the masses, due to its all-explaining nature and commercial as well as innovative viability.
And Machine Learning is just a shadow of Data Science. To take your career as high as you can’t even imagine, you can become competent in both these fields, which will enable you to analyse a frightening amount of data, and then proceed to extract value and provide insight on the data.
Moreover, in many organisations, ML engineers and Data Scientists work together on products, so it is likely that you will be exposed to the Data Scientists’ perspective if you’ve already become an ML engineer. An ML engineer salary and a data scientist salary do not have a vast difference. Both salaries are at an average of INR 12,50,000 p.a.
Future of Machine Learning in India
Machine Learning is the up-and-coming technology along with Artificial Intelligence that has taken over all industries. It provides every machine with the ability to gain knowledge, which helps it operate as well as a human being. According to Fortune Business Insights, the global market for machine learning in 2024 is valued at $21.17 billion. This may increase to $209.91 billion in the coming years, by 2029.
Machine Learning may be a subcategory of AI, however, it has proved useful in all segments of society and transformed the world. It is hard to imagine a future where there is no ML or AI. Let’s discuss the potential future of ML. The machine learning salary may be lower in India compared to other countries, but your experience can help make that change.
In addition to its incredible growth potential, machine learning is disrupting numerous industries as well. Providing inhuman speed and accuracy, machine learning is arguably one of our best allies because it allows entrepreneurs to make accurate decisions, and developers to see problems from new perspectives, and solve them more effectively.
PWC conducted a survey in 2021 that found 86% of individuals said machine learning and artificial intelligence have become part of their daily work routine. The COVID-19 pandemic has impacted businesses globally, according to over 50% of them.
Here is how this technology will help with future plans –
- Handling Large Databases – Do you know what “Big Data” is? Within the modern world, it pertains to the enormous volumes of data that are produced and accessible by almost every company. We cannot manage the vast amount of data streaming using modern machines. Then, how are we expected to interpret and analyze it? Machine learning is the solution. It fully automates the generation, storage, retrieval, and analysis of data efficiently.
- Learning capabilities – The majority of ML algorithms are built to function better as they filter through further data. For instance, suggestion engines are made to suggest “items” to consumers based on what they would most likely find interesting. Examples of websites and apps that make use of recommender systems include Youtube, Netflix, and Amazon. In fact, 75% of Netflix viewers are driven by the help of Machine learning.
- 24-hour operations – Algorithms for machine learning are like bots that can operate nonstop for 24 hours a day, seven days a week, 365 days a year, without ever getting tired or requiring to recharge.
With technologies like MLOps and AutoML, ML significantly contributes to the automation of business processes.
Being acquainted with new technologies like ML and AI can help you get some amazing machine learning jobs salary according to your experiences.
Popular AI and ML Blogs & Free Courses
Tips to Expand Your Machine Learning Expertise
If you want to become a machine learning engineer and take high package machine learning engineer salary in India ace the role, you should be mindful of the following tips:
Keep Practicing
Becoming skilled in any task demands regular dedication. Nothing beats gaining hands-on experience with actual projects when you are looking forward to increasing your machine learning engineer salary. You’ll find countless online sources brimming with machine learning projects to sharpen your abilities, making it a breeze to discover one that resonates with your passions.
Once you have chosen your project, dive right in and start tackling it. As you work your way through the project, make sure you monitor your progress. This will help you track your development and review your achievements in the future.
Take Part in Events and Workshops
In order to truly increase your machine learning engineering salary, honing coding skills is essential. However, it is equally important to develop a thorough comprehension of the multifaceted tools and technologies utilized within the practice. Immerse yourself in industry events and workshops to effectively broaden your understanding of these tools. Luckily, there are numerous free or budget-friendly events that grant access to industry experts and enable growth for machine learning engineers.
Become Part of a DevOps Community
Active participation in the machine learning community will help you stay up to date on the latest developments. You will also have the chance to exchange knowledge with other experts in the field.
On top of that, these machine learning communities offer the chance to make meaningful contributions to open-source projects. Therefore, you will be equipped with valuable experience and a noteworthy addition to your professional repertoire.
Concluding thoughts…
When it comes to the annual salary package, it must be admitted that compared to other tech-developed nations like the US and UK, salaries of ML and AI professionals in India is much less.
However, according to the ‘Salary Study-2018’ by Analytics India Magazine, nearly 40% of professionals in the field of Data Science and Analytics fetched an annual salary package over Rs.10 lakhs. So, it cannot be denied that in India, the salary scale is upscaling as well. Other factors aside, if you acquire the necessary Data Science and ML skills, your future in the industry will be very bright.
We hope you liked our article on Machine Learning salary in India. These numbers above are not set in stone. The real influencer of your salary is the skills you have, the mastery you have attained over them, and how quickly you grow and make the company grow as well. With the right kind of training and guidance, you can land a job with a great machine learning engineer salary.
You can also check IIT Delhi’s Executive PG Programme in Machine Learning in association with upGrad. IIT Delhi is one of the most prestigious institutions in India. With more the 500+ In-house faculty members which are the best in the subject matters.
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