NLP Career Path: Jobs in Natural Language Processing

Natural language processing (NLP) is a dynamic emerging field within artificial intelligence (AI) that allows computers and AI models to understand human language. This technology powers smart home devices you can control with your voice, text generators like ChatGPT, and solutions for industries from health care to marketing. If you want to explore careers in a growing AI field, a career in natural language processing might be a good choice for you. 

Explore an NLP career path to get a sense of what your career might look like, starting with entry-level jobs that don’t require prior experience and progressing through to NLP leadership roles. 

What is natural language processing?

Natural language processing (NLP) is the technology that allows computers and robots to understand and respond to what you say to them. To accomplish this understanding of human language, NLP engineers and scientists use machine learning and artificial intelligence to create NLP models with a deep understanding of language patterns. These models use statistics and probability to manipulate and comprehend language in various ways, such as generating text or verbal language, summarizing long documents, or analyzing the emotions behind written words. 

NLP applications across industries

NLP engineers and scientists have developed many different applications for NLP technology. You can explore NLP use cases in industries like finance, health care, data analysis, and marketing, as well as for personal and everyday uses like email filtering and smart assistants. 

• Finance: Financial professionals can use NLP to process a vast amount of financial data and summarize or make predictions about the future. 

• Health care: Medical professionals and people working in health care can use NLP in many ways, including analyzing patient records, writing or summarizing medical research papers, and helping health care workers make data-driven decisions quickly. 

• Data analysis: Data scientists can use NLP to speak conversationally with an AI agent trained on their data. NLP can also make predictions about effective visualizations for a data set. 

• Marketing: Marketing professionals can use NLP to analyze people’s online discussions about their brand, such as in online reviews or when people mention their brand or product on social media. NLP can offer insight into whether these comments have a positive or negative sentiment, providing a marketer with data they can use to fine-tune their marketing strategy. 

• Smart tech: Natural language processing is the technology that allows your email account to tell the difference between spam and emails you might care about. You also use NLP when you converse with a smart assistant like Alexa or Siri. 

NLP career path

With so many different ways that companies and organizations can use natural language processing, you can pursue an NLP career working on various projects. If you are new to the field, you may start in an entry-level job like a junior NLP engineer. After gaining experience or advanced education, you will likely move forward into positions with more responsibility. Later in your career, you may qualify for a leadership or director role on your team. Explore what your NLP career path might look like. 

Is NLP a good career path?

Natural language processing is a growing industry, and jobs in the field are predicted to grow over the next decade. Although the US Bureau of Labor Statistics doesn’t specifically track NLP jobs, you can look at categories like data scientists and computer research scientists to get a sense of how quickly the field is growing. The BLS projects that data scientist careers will grow by 36 percent and computer and information research scientist jobs will grow by 26 percent in the next decade [1, 2]. You can also get a sense of the amount of growth in the field by looking at the market size of the natural language processing industry worldwide: Statista predicts it will reach $48.31 billion in 2025 and grow to $156.8 billion by 2030 [3].

Entry-level NLP jobs

You may be able to start working in an entry-level natural language processing job after earning an associate’s degree, although it’s common for professionals in this field to start in the field with a bachelor’s degree. You can begin with an entry-level job for practical experience you can use to continue your career path. Two entry-level careers in NLP to explore are junior NLP engineer and junior data analyst. 

Junior NLP engineer

Average annual salary in the US (Glassdoor): $97,208 [4]

Job outlook (projected growth from 2023 to 2033): 36 percent [5]

As a junior NLP engineer, you will work with a team of other NLP professionals to design and develop natural language processing systems. In this role, some of your job duties will include preprocessing data and supporting more senior engineers to implement NLP algorithms. 

Junior data analyst

Average annual salary in the US (Glassdoor): $74,013 [6]

Job outlook (projected growth from 2023 to 2033): 36 percent [5]

As a junior data analyst, you will play a supportive role on a data analytics team. Some of your job responsibilities will include collecting and processing data, creating data visualizations, and writing reports of your team’s findings. 

Mid-level positions in NLP

As you start to gain experience or pursue advanced degrees, you may qualify for more highly paid jobs with more responsibility. In the middle of your career, you will develop your skills with NLP and machine learning techniques and begin to take on leadership roles. Two mid-level careers for NLP professionals include NLP engineer and conversational AI developer. 

NLP engineer

Average annual salary in the US (Glassdoor): $123,306 [7]

Job outlook (projected growth from 2023 to 2033): 36 percent [5]

As an NLP engineer, you will design, build, train, test, and refine natural language processing models. You may work with a team of other professionals to integrate NLP technology into software and other development projects. 

Conversational AI developer

Average annual salary in the US (Glassdoor): $106,449 [8]

Job outlook (projected growth from 2023 to 2033): 17 percent [9]

As a conversational AI developer, you will have a similar job to an NLP engineer working to design and create NLP models and algorithms, but you will focus on chatbots and conversational machines, which are AI models people can talk to. 

Senior-level jobs in NLP

To move into a senior job in natural language processing, you’ll need to gain many years of experience in the field or advanced degrees like a master’s or doctorate. At this level, you will take on a leadership role or may advance to a position directing a department. Two potential careers to consider for later in your NLP career path include senior NLP researcher and director of NLP engineering. 

Senior NLP researcher

Average annual salary in the US (Glassdoor): $143,157 [10] 

Job outlook (projected growth from 2023 to 2033): 36 percent [5]

As a senior natural language processing researcher, you will design and conduct research experiments, lead a research team, and use the scientific process to develop NLP solutions. You will also share your findings with stakeholders in your organization or the greater scientific community. 

Director of NLP engineering

Average annual salary in the US (Glassdoor): $187,662 [11]

Job outlook (projected growth from 2023 to 2033): 6 percent [12]

As the director of NLP engineering, you will lead the NLP engineering department to meet your company or organization’s goals. You will help set your team's NLP strategy and ensure that the NLP models your team creates provide value. 

Prepare for your NLP career path on Coursera.

With a career in natural language processing, you can help influence how NLP technology evolves and find new ways to apply this technology to daily life. If you want to explore getting started in this field, consider building your skills and knowledge base on Coursera. For example, you can explore NLP technology with the Natural Language Processing Specialization offered by Deep Learning.AI. You can also explore role-specific Professional Certificates to help you enhance your skills to prepare for a new career, like the IBM AI Engineering Professional Certificate.