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Natural Language Processing Jobs in Washington, DC

1872 Consulting

NLP Developer

Herndon, VA · On-site

The role involves designing and implementing machine learning solutions, particularly in Natural Language Processing, to enhance the effectiveness of Spectra AI and support the automated monitoring ...

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Natural Language Processing information

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$16

$28

$54

How much do natural language processing jobs pay per hour?

As of Sep 3, 2026, the average hourly pay for natural language processing in Washington, DC is $28.85, according to ZipRecruiter salary data. Most workers in this role earn between $19.86 and $33.51 per hour, depending on experience, location, and employer.

What is a natural language processing?

A Natural Language Processing (NLP) job involves developing and improving algorithms that enable computers to understand, interpret, and generate human language. Professionals in this field work on tasks like speech recognition, text analysis, machine translation, and chatbot development. They often use machine learning, deep learning, and linguistic principles to build and refine NLP models. NLP experts commonly work in industries such as healthcare, finance, and technology to enhance communication and automate language-related tasks.

What are the key skills and qualifications needed to thrive in natural language processing, and why are they important?

To thrive in Natural Language Processing, you need strong expertise in linguistics, statistics, and machine learning, typically supported by a degree in computer science, computational linguistics, or a related field. Familiarity with tools and frameworks such as Python, TensorFlow, PyTorch, spaCy, and NLP libraries, as well as certifications in data science or NLP, are valuable assets. Analytical thinking, problem-solving skills, and the ability to collaborate across multidisciplinary teams are highly desirable. These competencies are essential for developing powerful language models, extracting meaningful insights from data, and delivering effective real-world solutions in language technology.

What are some typical challenges faced by professionals in natural language processing?

Professionals in Natural Language Processing (NLP) often encounter challenges such as understanding ambiguities in human language, managing large and unstructured datasets, and keeping up with rapid advances in NLP methodologies. They may also need to fine-tune models for domain-specific contexts and ensure solutions meet ethical and privacy guidelines. Collaboration with data scientists, linguists, engineers, and product teams is common, requiring strong communication skills. Successfully tackling these challenges is a critical part of developing robust NLP applications that add meaningful value to users and businesses.

How to get a job in Natural Language Processing?

To get a job in Natural Language Processing (NLP), candidates typically need a strong background in computer science, linguistics, or related fields, along with proficiency in programming languages like Python and experience with NLP libraries such as NLTK or spaCy. Gaining practical experience through projects, internships, or research, and obtaining relevant certifications can improve employability. A solid understanding of machine learning, deep learning, and data analysis is also beneficial for NLP roles.

Is natural language processing a good career?

Natural Language Processing (NLP) is a growing field within artificial intelligence that involves developing algorithms to understand and generate human language. It offers opportunities in industries such as tech, healthcare, and finance, often requiring skills in machine learning, programming, and linguistics. The demand for NLP professionals is increasing, making it a promising career choice for those interested in AI and language technologies.

What can I do with natural language processing?

A natural language processing (NLP) professional develops systems that enable computers to understand, interpret, and generate human language. This includes tasks like sentiment analysis, language translation, chatbots, and speech recognition, often using tools like Python, NLP libraries, and machine learning techniques. NLP roles require strong programming skills and knowledge of linguistics or data science.

What are the most commonly searched types of Natural Language Processing jobs in Washington, DC?

The most popular types of Natural Language Processing jobs in Washington, DC are:

What are popular job titles related to Natural Language Processing jobs in Washington, DC?

For Natural Language Processing jobs in Washington, DC, the most frequently searched job titles are:

What job categories do people searching Natural Language Processing jobs in Washington, DC look for?

The top searched job categories for Natural Language Processing jobs in Washington, DC are:

Natural Language Processing jobs near you
Infographic showing various Natural Language Processing job openings in Washington, DC as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 19% Part Time, 1% Temporary, and 3% Contract. Highlights an 92% Physical, 1% Hybrid, and 7% Remote job distribution, with an average salary of $60,012 per year, or $28.9 per hour.

Natural Language Processing Engineer

Beyond SOF

Washington, DC • On-site

Full-time

Re-posted 27 days ago

Job description

Role Summary:
The Natural Language Processing
(NLP) Engineer is responsible for
developing and implementing NLP
solutions to support the
company's projects.
Main Responsibilities and duties:
Develop and implement NLP
solutions.
Collaborate with the engineering
team to integrate NLP solutions
into projects.
Conduct research on NLP
technologies and trends.
Stay updated on the latest NLP
technologies and trends.
Develop and implement
quantum-enhanced NLP
solutions. Collaborate with
quantum engineers to integrate
quantum technologies into NLP
projects.

Apply