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Natural Language Processing Jobs in Seattle, WA (NOW HIRING)

PitchBook Data

Machine Learning Engineer

Seattle, WA · On-site

Your focus will span across natural language processing (NLP), generative AI (GenAI), large language models (LLMs), and scalable data systems. You will be expected to tackle complex technical ...

Ai2

Research Scientist, Agents for Science

Seattle, WA · On-site

Required : • A PhD focusing on machine learning, reasoning, natural language processing, or a related area, with expertise in one or more of the following: reinforcement learning, experimental ...

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Natural Language Processing information

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$16

$29

$55

How much do natural language processing jobs pay per hour?

As of Sep 5, 2026, the average hourly pay for natural language processing in Seattle, WA is $29.10, according to ZipRecruiter salary data. Most workers in this role earn between $20.05 and $33.80 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 Seattle, WA?

The most popular types of Natural Language Processing jobs in Seattle, WA are:

What are popular job titles related to Natural Language Processing jobs in Seattle, WA?

For Natural Language Processing jobs in Seattle, WA, the most frequently searched job titles are:

What job categories do people searching Natural Language Processing jobs in Seattle, WA look for?

The top searched job categories for Natural Language Processing jobs in Seattle, WA are:

What cities near Seattle, WA are hiring for Natural Language Processing jobs?

Cities near Seattle, WA with the most Natural Language Processing job openings:

Natural Language Processing jobs near you
Infographic showing various Natural Language Processing job openings in Seattle, WA as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 20% Part Time, 1% Temporary, and 4% Contract. Highlights an 93% Physical, 1% Hybrid, and 6% Remote job distribution, with an average salary of $60,536 per year, or $29.1 per hour.

Sr. Manager of Applied Science - Catalog Services, Product Knowledge GenAI

Amazon

Seattle, WA • On-site

$144K - $190K/yr

Full-time

Re-posted 12 days ago

Key responsibilities

  • Manage business and technical requirements, coordinate program activities, and serve as the primary point of contact for stakeholders worldwide.

  • Partner with scientists, economists, and engineers to deliver scalable machine learning models and build mechanisms for customer insights.

  • Manage and develop a team of Applied Scientists to produce scientific, engineering, and business best practices.

Amazon rating

7.4

Company rating: 7.4 out of 10

Based on 7,147 frontline employees who took The Breakroom Quiz

5th of 39 rated national retailers

Job description

The Catalog Services Product Knowledge team is seeking a Sr. Applied Science Manager for leading initiatives for understanding, and scaling organization of product schema information. Our vision is simple: build AI systems that are capable of a deep product understanding, so we can organize and scale the catalog metadata (schema) for Amazon e-commerce catalog worldwide.

This is a complex problem because the magnitude of products entities (attributes, values, constraints) to be modeled to cover all the Amazon products worldwide. You will lead a team of experienced Applied Scientists (direct reports) to create models and deliver them into the Amazon production ecosystem. Your efforts will build a robust ensemble of ML and GenAI techniques that will scale our catalog artifacts with a high precision across countries and languages.


The leader will drive investments in machine learning, natural language processing, GenAI, to solve real world problems at scale. The team's output affects the velocity at which we build product schema and support the largest e-commerce catalog and impact million of customers. The team builds solutions ranging from automatic generation of product metadata, classification of entities, validation of concepts against customer traffic, creation of agents solving complex tasks mimicking human decisions at high precision, etc; all these developments drive true understanding of products at scale.


We are looking for an entrepreneurial, experienced Sr. Applied Science Manager who can turn a group of Machine Learning Scientists (PhD's in NLP, ML, GenAI) to produce best in class solutions. The ideal candidate has deep expertise in one or several of the following fields: Generative AI, Agents, LLMs, Web search, Applied/Theoretical Machine Learning, Deep Neural Networks, Classification Systems, Clustering, Natural Language Processing.

S/he has a strong publication record at relevant academic venues and proven experience in launching products/features in the industry.
Key job responsibilities
In this team, you will:
- Manage business and technical requirements, design, be responsible for the overall coordination, quality, productivity and will be the primary point of contact for world-wide stakeholders of programs and goals that you lead.
- Partner with scientists, economists, and engineers to help deliver scalable ML scaled models, while building mechanisms to help our customers gain and apply insights, and build road maps for the projects you own.
- Track service levels and schedule adherence, and ensure the individual stakeholder teams meet and exceed their performance targets.
- Be expected to discover, define, and apply scientific, engineering, and business best practices.
- Manage and develop Applied Scientists (direct reports with a respective team).
About the team
The team's mission is to infer knowledge, understand, and derive product schema for all Amazon products entering the Catalog. The work is critical to power drive policies on how products will be merchandised, guide Selling Partners, inform models how to infer attributes. All this information drives the navigational Taxonomy, Search and Detail Page experiences, impacting million of customers

This is an already formed team with experience leading programs spanning services and ML initiatives. The leader collaborates closely with Software Managers, Sr. Leaders, and has exposure to multiple peer teams at Amazon who rely on this team's developments.

What Amazon employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About Amazon

Sourced by ZipRecruiter

Amazon.com, Inc., commonly known as Amazon, is an American multinational technology company. It was founded by Jeff Bezos in 1994 and initially started as an online marketplace for books. Since then, Amazon has expanded its operations and become one of the largest e-commerce companies in the world. Amazon's primary business is its online retail platform, where customers can purchase a vast array of products, including electronics, clothing, books, home goods, and much more. The company offers a convenient and user-friendly shopping experience, with features such as fast shipping, customer reviews, and personalized recommendations. In addition to its e-commerce platform, Amazon has diversified its business into various other areas. One of its notable ventures is Amazon Web Services (AWS), a comprehensive cloud computing platform that provides services such as storage, compute power, and database management to individuals and businesses. AWS has become a leader in the cloud computing industry, powering many websites and applications worldwide. Amazon has also developed its own consumer electronics, including the popular Amazon Kindle e-reader, Fire tablets, Fire TV streaming devices, and the Alexa-powered Echo smart speakers. The Alexa voice assistant, integrated into these devices, allows users to interact with their devices using voice commands, perform tasks, and access information. Furthermore, Amazon has expanded into media and entertainment. It operates Prime Video, a streaming service that offers a wide range of movies, TV shows, and original content. Amazon Music provides a platform for streaming and purchasing digital music, while Audible offers audiobooks and other audio content. The company's commitment to customer satisfaction and convenience is demonstrated by its membership program, Amazon Prime. Prime members receive various benefits, including free two-day shipping, access to streaming services, exclusive deals, and more.

Industry

It services, book publishers, retail, real estate, computer and electronic product manufacturing and software development

Company size

10,000+ Employees

Headquarters location

Seattle, WA, US

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