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Natural Language Processing Engineer Jobs (NOW HIRING)

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Natural Language Processing Engineer information

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$49.5K

$92K

$142.5K

How much do natural language processing engineer jobs pay per year?

As of Jun 4, 2026, the average yearly pay for natural language processing engineer in the United States is $92,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $74,500.00 and $103,000.00 per year, depending on experience, location, and employer.

What does a Natural Language Processing Engineer do?

A Natural Language Processing (NLP) Engineer develops algorithms and models that enable machines to understand, interpret, and generate human language. They work with large datasets, train machine learning models, and fine-tune language models for applications like chatbots, speech recognition, and text analysis. NLP Engineers typically use programming languages like Python and frameworks such as TensorFlow, PyTorch, or spaCy. Their work involves data preprocessing, model training, and optimizing performance to enhance the accuracy and efficiency of language-based AI systems.

What are the key skills and qualifications needed to thrive in the Natural Language Processing Engineer position, and why are they important?

To thrive as a Natural Language Processing Engineer, you need strong programming skills (especially in Python), a solid understanding of machine learning and linguistics, and typically a degree in computer science, computational linguistics, or a related field. Familiarity with NLP libraries such as NLTK, spaCy, TensorFlow, or PyTorch as well as experience with cloud platforms and version control is often required. Analytical thinking, collaboration, and effective communication are important soft skills in this role. These competencies ensure the ability to build robust language models, contribute to innovative projects, and work efficiently in dynamic, cross-functional teams.

What does a typical day look like for a Natural Language Processing Engineer?

A typical day for a Natural Language Processing Engineer involves developing, testing, and refining language models and algorithms, often using real-world datasets. You might collaborate with data scientists, product managers, and software engineers to integrate NLP solutions into applications or address complex language-related challenges. Regular responsibilities include data preprocessing, feature engineering, model evaluation, and troubleshooting performance issues. Most NLP engineers work in a team-oriented, agile environment where clear communication and iterative development are key. This structure offers a dynamic workflow and opportunities to learn from others while making a tangible impact on the products you help build.
What cities are hiring for Natural Language Processing Engineer jobs? Cities with the most Natural Language Processing Engineer job openings:
What are the most commonly searched types of Natural Language Processing Engineer jobs? The most popular types of Natural Language Processing Engineer jobs are:
What states have the most Natural Language Processing Engineer jobs? States with the most job openings for Natural Language Processing Engineer jobs include:
Infographic showing various Natural Language Processing Engineer job openings in the United States as of May 2026, with employment types broken down into 63% Full Time, 31% Part Time, and 6% Contract. Highlights an 91% Physical, 2% Hybrid, and 7% Remote job distribution, with an average salary of $92,018 per year, or $44.2 per hour.
Natural Language Processing Engineer

Natural Language Processing Engineer

Beyond SOF

Washington, DC โ€ข On-site

Full-time

Posted 17 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.