NLP Engineer Salary in India in 2024 [For Freshers & Experienced]

In today’s technology-oriented world of digital communications, social media, and the internet of things, we generate a colossal amount of data every day. Text data constitute nearly 80 percent of this stockpile, capable of providing crucial insights to businesses.

Therefore, Natural Language Processing or NLP is gaining prominence in assisting data scientists with interpreting and analyzing this text data. In this article, we will help you understand the market demand for this branch of artificial intelligence and cover the latest NLP engineer salary trends. 

In this article, we will highlight some of the basic facts about NLP, and its importance in today’s world. Furthermore, you will also get to learn about some of the top machine learning engineer jobs, and natural language processing salary in India.

What is NLP?

Computers require extra support when it comes to handling unstructured datasets of human languages, which comprises different grammar languages, syntax, slangs, and dialects. NLP uses data and mathematics to help you engineer computers so that they can understand and interpret natural expressions. Learn more about natural language processing.

Why is it important?

Before we delve deeper into the various machine learning jobs and the natural language processing engineer salary, let’s take a look at some of the reasons that make NLP so popular in today’s world. Businesses often have to deal with massive amounts of unstructured text-heavy data. Therefore, they are always looking for various ways to process it efficiently. Infact, most of the information that is created online is natural human language. This is where natural language processing comes into play. It has proved to be quite an effective tool to effectively analyse all data. With the help of NLP, businesses can now drive valuable insights from all these analysed data for their brand performance. Additionally, NLP also helps to identify any persisting issues, and take the appropriate measures to mitigate the problems, thus improving performance. 

Advantages of NLP

Organisations can derive several benefits from implementing NLP in their business models. Some of them might include

• Improved Data Analysis

Analysing unstructured data like documents and emails, can be quite difficult and time-consuming at times. But with the help of NLP, you can now quite easily process and analyse large amounts of text-based data. Furthermore, you longer need to waste time and energy in performing repetitive tasks such as processing forms or collating surveys since the same can be done with NLP and with much more accuracy. NLP has also proven to be quite beneficial for recruiters since they can now screen hundreds and thousands of applications using this technology based on desired characteristics. Thus, recruiters no longer need to spend an enormous amount of time reviewing the forms of every candidate, which in turn saves up a lot of time and money.  

• Better Customer Experience 

Yet another popular advantage of deploying Natural Processing Language applications is that it helps organisations provide a much better and improved customer experience. For example, NLP chatbots can now quite easily analyze and understand sentence structure and utilise other machine-learning methods in their operations to ensure a smooth process. Thus, customers no longer need to wait for hours to get back a response since the same can be done within minutes with the help of chatbots. This not only makes the consumers feel important but also helps to create a positive customer experience.

• Reduced Cost

Cost and time are two essential ingredients for running a successful business. But what if you could manage both these factors and, infact, reduce their consumption significantly without impacting business? Natural Language Processing helps you achieve the same. You no longer need to implement six people to respond to customer requests since the same can be done by implementing an NLP solution. It helps to carry out day-to-day operations in a more efficient manner, which in turn leads to improved performance. Furthermore, enterprise AI also delivers accurate insights, which can further be used to improve the customer experience. Exploring various such significant insights enables natural language processing salary to grow more and more with time. 

With that said, let’s take a look at some of the top machine learning engineer jobs that are mentioned below. You will also get to know the average Natural Language processing engineer salary in India. 

NLP applications

NLP solutions deliver immense value for organizations across different sectors, from digital communications to healthcare and medicine to finance, marketing, and retail. Here are some of the most common applications of NLP in the industry today:

• Spell checks
• Chatbots
• Text classification 
• Automatic summary generation
• Language identification
• Sentiment analysis
• Market intelligence
• Virtual assistance (for example, Alexa and Siri)

Read more: NLP Applications for Businesses

Jobs related to NLP engineering

NLP is an emerging technology that lies at the intersection of data science, machine learning, and artificial intelligence. According to a World Economic Forum study, the proliferation of machines and algorithms will create 133 million new jobs by 2022. 

Moreover, the future will hold many opportunities for experienced professionals and those with the right training in the AI/ML space. The ‘Future of Jobs in India’ report by EY and Nasscom estimated that 9% of our workforce would be employed in roles that require new skill sets. 

NLP engineering is concerned with designing and developing systems and defining appropriate datasets for language learning. Companies typically hire NLP engineers to undertake the following tasks:

• To engineer a device capable of understanding human language and completing an action.
• To create computers that can analyze and generate human languages, including speech functions.
• Build computer programs and applications to understand the spoken human language.

Generally, recruiters look for people who possess a strong aptitude in mathematics and statistics. They want someone who knows the ins and outs of data modeling and engineering structures. 

They also prefer candidates who can identify and implement new technologies while working with the company. For example, a banking company hires you to develop a downloadable app with voice-activated capabilities to serve its customers better. While structuring the NLP components of your app and referring to the consumer data, you may come across another voice-activated feature that can trump your competitors. 

If you look at the current NLP engineer salary figures across the industry, you will notice that employers are offering attractive remuneration and incentives to reward and encourage the job market entrants. 

Read: Machine Learning Engineer Salary in India

Some of the various career paths that you can explore in Natural Language Processing might include, 

• Senior Data Scientist
• Python Developer
• Machine Learning Engineer
• Technical Architect
• Speech Engineer and
• Associate Technical Lead among others. 

NLP salary in India

In this section, we will infer the average pay of various NLP related career paths from two leading search engines for worldwide job listings, Indeed and PayScale. These websites perform their calculations and estimations using data from past and present job advertisements. In general, NLP engineering jobs mention machine learning, data analysis, Python, R, statistical analysis, etc. as the desired skills. Also, the paying capacity of companies varies across different geographical locations.

Upon observing the individual job positions listed on Indeed, we find the following things:

1. Data Science Intern

Role: Performing exploratory data analysis, researching new algorithms and machine learning approaches, and assisting a team of professionals in conducting analyses and solving problems.

Average salary: ₹ 13,966 per month 

Source

2. Data Scientist

Role: Designing data modeling processes to collect, clean, process raw data, and aiding data analysis tasks.

Average salary: ₹ 6,69,628 per year

Source

Learn more: Data Scientist Salary in India

3. Research Engineer

Role: Analyzing, implementing, and testing the instruments and devices in research labs. Additionally, they may be involved in writing grant proposals and maintaining contact with research sponsors. 

Average salary: ₹ 31,328 per month

Source

4. Test lead/manager

Role: Guiding and monitoring the design and execution of testing efforts. They also ensure whether the test resources are planned and managed adequately. 

Average salary: ₹ 9,00,035 per year

Source

FYI: Free nlp online course!

5. Junior Data Scientist

Role: Applying different data science techniques to extract valuable insights from data and contribute to achieving business goals. 

Average salary: ₹ 788,460 per year

Source

6. Senior Data Scientist  

If you move up the engineer ranks and gain five to nine years of professional experience in a data scientist role, you can become a senior data scientist. The average total compensation at this mid-career level will be higher than your previous salary. On spending more than ten years in this field, you can expect an annual pay grade as high as ₹30 lakh. Your pay package would depend on the skill level and technical expertise relevant to the company’s needs. 

Average annual salary: ₹14,68,688

Source

7. Machine Learning Engineer

An ML engineer is responsible for training and creating data models. Their work involves automating processes like speech recognition, image classification, marketing forecasting, and many others. This process requires exceptional mathematical, statistical, and programming skills. You can start at the entry-level, move on to senior designations, making upwards of a seven-figure yearly salary in Indian currency.

Average annual salary: ₹692,363

Source

Learn more: Machine Learning Salary in India

8. Software Developer

As a software developer, you build computer applications or other devices that can perform specific tasks. Usually, they work directly with vendors, clients, or users. Software developers must keep abreast of the technological changes in different systems and learn about the best practices in development. To update their knowledge, they can attend workshops from time to time. 

Additionally, they may be required to convey technical information to employees from other backgrounds. Coaching and mentoring junior software developers can help develop the requisite communication skills for this purpose.

Average annual salary: ₹487,129

Source

Learn more: Software Developer Salary in India

9. Senior Software Engineer

Besides the requirements listed above, senior software engineers should be an efficient multitasker and have qualities like strong attention to detail. They need to stay focused on the job at hand, working independently as well as a part of the team. 

First and foremost, software engineers require adequate knowledge and familiarity with web coding, such as Javascript, CSS, and HTML. Other requirements include technical, managerial, and supervisory skills to take care of the following responsibilities:

• Translate business requirements into technical specifications
• Test and document applications for clients
• Write, modify, and debug software 
• Review the work of junior engineers
• Plan project timelines to deliver quality products to clients

Average annual salary: ₹876,252

Source

NLP engineering is an ever-evolving career. And you can steadily work your way up the ladder and advance to higher ranks on the back of your technical competence. For instance, you can take up a full-stack engineering role wherein you will design and develop software for the backend and frontend of applications.

If you are interested in research, you can become a research scientist or manager, overseeing the tech and research teams in your organization. Such senior-level positions come with greater flexibility, responsibility, and pay scales. 

Global trends in NLP engineering

• The global market has benefitted from major architecture breakthroughs, including attention mechanisms like transformer models and BERT.
• We have experienced considerable growth in the use of convolutional and recursive neural networks, reinforcement learning, unsupervised learning, deep generative models, etc.
• Innovative techniques, earlier restricted to the research arena alone, are now becoming more mainstream via several business applications.
• AI/ML job profiles continue to evolve, and companies are paying lucrative NLP engineer salary.

A quick snapshot of what we learned

In this article, we covered how NLP is becoming a game-changer for computer science and business intelligence. We also examined the technology’s scope and explored the different types of job roles in the market today. We then looked at the NLP salary in India and concluded with some emerging trends in this engineering field.

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