Key job responsibilities Design and develop data annotation guidelines and workflows. Manage and ... Collaborate with scientists, engineers, and product managers in defining metrics, guidelines, and ...
Key job responsibilities Design and develop data annotation guidelines and workflows. Manage and ... Collaborate with scientists, engineers, and product managers in defining metrics, guidelines, and ...
Key job responsibilities Design and develop data annotation guidelines and workflows. Manage and ... Collaborate with scientists, engineers, and product managers in defining metrics, guidelines, and ...
Key job responsibilities Design and develop data annotation guidelines and workflows. Manage and ... Collaborate with scientists, engineers, and product managers in defining metrics, guidelines, and ...
Handle annotation & data investigation requests from multiple stakeholders with high efficiency and quality in a fast-paced environment. Collaborate with scientists, engineers, and product managers ...
Handle annotation & data investigation requests from multiple stakeholders with high efficiency and quality in a fast-paced environment. Collaborate with scientists, engineers, and product managers ...
Catalog Specialist, RCX
Bellevue, WA · On-site
WW R&R includes business, product, operations, data, and software engineering teams, who together ... Perform data annotation required to train and evaluate ML models effectively • Support data ...
Catalog Specialist, RCX
Bellevue, WA · On-site
WW R&R includes business, product, operations, data, and software engineering teams, who together ... Perform data annotation required to train and evaluate ML models effectively • Support data ...
Catalog Specialist, RCX
Bellevue, WA · On-site
WW R&R includes business, product, operations, data, and software engineering teams, who together ... Perform data annotation required to train and evaluate ML models effectively • Support data ...
Catalog Specialist, RCX
Bellevue, WA · On-site
WW R&R includes business, product, operations, data, and software engineering teams, who together ... Perform data annotation required to train and evaluate ML models effectively • Support data ...
Catalog Specialist, RCX
Bellevue, WA · On-site
WW R&R includes business, product, operations, data, and software engineering teams, who together ... Perform data annotation required to train and evaluate ML models effectively Support data ...
Catalog Specialist, RCX
Bellevue, WA · On-site
WW R&R includes business, product, operations, data, and software engineering teams, who together ... Perform data annotation required to train and evaluate ML models effectively Support data ...
Catalog Specialist, RCX
Bellevue, WA · On-site
WW R&R includes business, product, operations, data, and software engineering teams, who together ... Perform data annotation required to train and evaluate ML models effectively Support data ...
Catalog Specialist, RCX
Bellevue, WA · On-site
WW R&R includes business, product, operations, data, and software engineering teams, who together ... Perform data annotation required to train and evaluate ML models effectively Support data ...
Catalog Specialist, RCX
Bellevue, WA · On-site
WW R&R includes business, product, operations, data, and software engineering teams, who together ... Perform data annotation required to train and evaluate ML models effectively Support data ...
Catalog Specialist, RCX
Bellevue, WA · On-site
WW R&R includes business, product, operations, data, and software engineering teams, who together ... Perform data annotation required to train and evaluate ML models effectively Support data ...
Catalog Specialist, RCX
Bellevue, WA · On-site
WW R&R includes business, product, operations, data, and software engineering teams, who together ... Perform data annotation required to train and evaluate ML models effectively Support data ...
Catalog Specialist, RCX
Bellevue, WA · On-site
WW R&R includes business, product, operations, data, and software engineering teams, who together ... Perform data annotation required to train and evaluate ML models effectively Support data ...
They will lead and drive the requirements behind data annotation tasks and tooling, writing ... They will work in close collaboration with other Language Engineers, AI Editors, Product Managers ...
They will lead and drive the requirements behind data annotation tasks and tooling, writing ... They will work in close collaboration with other Language Engineers, AI Editors, Product Managers ...
They will lead and drive the requirements behind data annotation tasks and tooling, writing ... They will work in close collaboration with other Language Engineers, AI Editors, Product Managers ...
They will lead and drive the requirements behind data annotation tasks and tooling, writing ... They will work in close collaboration with other Language Engineers, AI Editors, Product Managers ...
They will lead and drive the requirements behind data annotation tasks and tooling, writing ... They will work in close collaboration with other Language Engineers, AI Editors, Product Managers ...
They will lead and drive the requirements behind data annotation tasks and tooling, writing ... They will work in close collaboration with other Language Engineers, AI Editors, Product Managers ...
Senior Software Engineer, Backend
$142K - $263K/yr
... AIML Annotation Platform team provides frameworks and services for enabling effective data ... Engage in code review, pair programming and architecture discussions with other members of the team.
Senior Software Engineer, Backend
$142K - $263K/yr
... AIML Annotation Platform team provides frameworks and services for enabling effective data ... Engage in code review, pair programming and architecture discussions with other members of the team.
Staff Data Engineer
Seattle, WA · On-site
$130K - $156K/yr
Labels & Annotation Data Lifecycle: Own how labels and semantic annotations are appended to ... Set the data-engineering standards for the flywheel schema conventions, dataset contracts, quality ...
Staff Data Engineer
Seattle, WA · On-site
$130K - $156K/yr
Labels & Annotation Data Lifecycle: Own how labels and semantic annotations are appended to ... Set the data-engineering standards for the flywheel schema conventions, dataset contracts, quality ...
Staff Data Engineer
Seattle, WA · On-site
$130K - $156K/yr
Labels & Annotation Data Lifecycle: Own how labels and semantic annotations are appended to ... Set the data-engineering standards for the flywheel schema conventions, dataset contracts, quality ...
Quick apply
Staff Data Engineer
Seattle, WA · On-site
$130K - $156K/yr
Labels & Annotation Data Lifecycle: Own how labels and semantic annotations are appended to ... Set the data-engineering standards for the flywheel schema conventions, dataset contracts, quality ...
Staff Data Engineer
Seattle, WA · On-site
Labels & Annotation Data Lifecycle: Own how labels and semantic annotations are appended to ... Set the data-engineering standards for the flywheel schema conventions, dataset contracts, quality ...
Staff Data Engineer
Seattle, WA · On-site
Labels & Annotation Data Lifecycle: Own how labels and semantic annotations are appended to ... Set the data-engineering standards for the flywheel schema conventions, dataset contracts, quality ...
... data annotation and quality validation activities * Maintain accurate operational records and logs Continuous Improvement * Provide feedback on robot performance and usability * Assist engineering ...
Quick apply
... data annotation and quality validation activities * Maintain accurate operational records and logs Continuous Improvement * Provide feedback on robot performance and usability * Assist engineering ...
... data annotation and quality validation activities * Maintain accurate operational records and logs Continuous Improvement * Provide feedback on robot performance and usability * Assist engineering ...
... data annotation and quality validation activities * Maintain accurate operational records and logs Continuous Improvement * Provide feedback on robot performance and usability * Assist engineering ...
... Collaborate with engineers, data scientists, and researchers to share findings and strengthen ... with structured data annotation and rubric-based scoring • Prior work in trust and safety ...
... Collaborate with engineers, data scientists, and researchers to share findings and strengthen ... with structured data annotation and rubric-based scoring • Prior work in trust and safety ...
Machine Learning Data Linguist, Alexa AI
Seattle, WA · On-site
$130K - $156K/yr
This role focuses on language data, primarily in the areas of text annotation and general data analysis deliverables. The ML Data Linguist must have a passion for data, efficiency, accuracy, and ...
Machine Learning Data Linguist, Alexa AI
Seattle, WA · On-site
$130K - $156K/yr
This role focuses on language data, primarily in the areas of text annotation and general data analysis deliverables. The ML Data Linguist must have a passion for data, efficiency, accuracy, and ...
Data Annotation Engineer information
See Everett, WA salary details
$56.9K - $71.5K
2% of jobs
$71.5K - $86.1K
9% of jobs
$96.3K is the 25th percentile. Wages below this are outliers.
$86.1K - $100.7K
20% of jobs
$100.7K - $115.3K
4% of jobs
$115.3K - $130K
4% of jobs
$130K - $144.6K
1% of jobs
$144.6K - $159.2K
0% of jobs
$159.2K - $173.8K
0% of jobs
The median wage is $181.1K / yr.
$173.8K - $188.4K
18% of jobs
$188.4K - $203K
0% of jobs
$208.7K is the 75th percentile. Wages above this are outliers.
$203K - $217.6K
41% of jobs
$56.9K
$162.9K
$217.6K
How much do data annotation engineer jobs pay per year?
As of Jul 18, 2026, the average yearly pay for data annotation engineer in Everett, WA is $162,896.00, according to ZipRecruiter salary data. Most workers in this role earn between $92,800.00 and $216,500.00 per year, depending on experience, location, and employer.
What are the main challenges faced by Data Annotation Engineers in their daily work?
One of the main challenges Data Annotation Engineers face is ensuring consistent accuracy and quality in labeling large and often complex datasets. Attention to detail is critical, as even small errors can significantly affect machine learning model performance. Additionally, engineers must frequently adapt to evolving annotation guidelines and emerging data types, which requires ongoing learning and flexibility. Collaboration with data scientists and project managers is common to clarify requirements and resolve ambiguities, making strong communication skills essential for success.
What are the key skills and qualifications needed to thrive in the Data Annotation Engineer position, and why are they important?
To thrive as a Data Annotation Engineer, you need a strong background in data analysis, attention to detail, and familiarity with annotation processes, often supported by a degree in computer science or a related field. Proficiency with annotation tools like Labelbox, CVAT, or VIA, and understanding of data formats used in machine learning, is commonly required. Excellent communication, collaboration, and organizational skills help you effectively manage projects and cooperate with cross-functional teams. These abilities are crucial for delivering high-quality labeled data, which directly impacts the performance of AI and machine learning models.
Does data annotation really pay?
Data annotation engineers can earn competitive wages, often paid hourly or per task, with pay rates varying based on experience, complexity of annotations, and the platform or employer. Entry-level roles may start at minimum wage, while experienced annotators or those with specialized skills can earn higher salaries or freelance rates. Overall, data annotation can provide a reliable income, especially for remote or flexible work arrangements.
What is the highest salary for data annotator?
The highest salary for a data annotation engineer can reach up to $80,000 to $100,000 annually, depending on experience, location, and the complexity of annotation tasks. Senior roles or those with specialized skills in tools like Labelbox or CVAT may earn higher compensation. Salaries vary widely across companies and regions but generally reflect the technical skills required for high-quality data labeling.
What is a data annotation engineer?
A data annotation engineer is a professional responsible for labeling and annotating data, such as images, text, or videos, to prepare it for machine learning models. They often use specialized tools and follow guidelines to ensure data quality, supporting the development of AI systems.
How hard is it to get hired by data annotation?
Getting hired as a data annotation engineer typically requires basic computer skills, attention to detail, and familiarity with annotation tools. Many positions are entry-level and may not require advanced degrees, but strong accuracy and consistency are important for success in the role.
What is a Data Annotation Engineer job?
A Data Annotation Engineer is responsible for labeling and annotating data—such as text, images, audio, or video—to train machine learning models. They ensure that data is accurately categorized and structured to improve model performance. This role often involves using specialized annotation tools, following detailed guidelines, and working closely with data scientists and AI teams. Data Annotation Engineers play a crucial role in the development of AI applications by providing high-quality labeled datasets for supervised learning.
What are popular job titles related to Data Annotation Engineer jobs in Everett, WA? For Data Annotation Engineer jobs in Everett, WA, the most frequently searched job titles are:
What job categories do people searching Data Annotation Engineer jobs in Everett, WA look for? The top searched job categories for Data Annotation Engineer jobs in Everett, WA are:
What cities near Everett, WA are hiring for Data Annotation Engineer jobs? Cities near Everett, WA with the most Data Annotation Engineer job openings:
Full-time
Re-posted 18 days ago
Amazon rating
7.4
Based on 6,974 frontline employees who took The Breakroom Quiz
6th of 39 rated national retailers
Job description
We are the MIDAS team within the Amazon Search organization. We own the end-to-end human annotation requirements for our product partners. This is an opportunity to join a high-performing team that helps customers worldwide find and discover the best products, meet their personalized needs with the right product details, and receive comparisons, recommendations, and more on Amazon.
This role is high-visibility and highly cross-functional, requiring collaboration and influence across global product, design, science, operations, and engineering teams.
We are looking for a Language Engineer to join MIDAS to write intuitive, labeler-friendly annotation guidelines that enable measurement of search quality, support data wrangling and analysis, define specifications for labeling UI templates, and report labeled-data quality metrics to deliver on stakeholder requirements and improve the customer experience. To achieve high accuracy and consistency in labeled data outputs, Language Engineers apply linguistic (e.g., semantics, syntax, pragmatics) and scripting expertise to solve natural language processing and language understanding challenges.
Key job responsibilities
Design and develop data annotation guidelines and workflows.
Manage and process large amounts of structured and unstructured data.
Adopt and design quality control metrics and methodology to evaluate the quality of data annotation.
Maximize productivity, process efficiency and quality through streamlined workflows, process standardization, documentation, audits and investigations on a periodic basis.
Handle annotation & data investigation requests from multiple stakeholders with high efficiency and quality in a fast-paced environment.
Collaborate with scientists, engineers, and product managers in defining metrics, guidelines, and workflows.
Initiate and contribute towards improvement projects, present solution proposals, and implement them.
Establish processes and mechanisms to onboard and train junior data associates on an ongoing basis.
Handle work prioritization and deliver based on business priorities.
Be flexible in changes to conventions deployed in response to customers' requests and change workflows accordingly.
About the team
Amazon is among the world's top 10 most-visited websites, and Amazon Search Organization sits at the center of how hundreds of millions of customers shop-processing billions of queries to find products. Within Amazon Search, the MIDAS team delivers high-quality labeled data at scale to train and evaluate AI models and produce metrics that measure customer experience
We operate with agility, deep linguistic expertise, strong data integrity, self-service enablement, and frugal use of resources. We partner closely with applied science, engineering, and product teams to improve semantic matching, ranking, computer vision, image processing, and augmented reality.
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 and computer and electronic product manufacturing
Company size
10,000+ Employees
Headquarters location
Seattle, WA, US