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Full Time Machine Learning Data Annotation Jobs in Seattle, WA

Q ANALYSTS LLC

Data Annotation Technician

Kirkland, WA · On-site +1

... AI) and machine learning (ML). Q Analysts is headquartered in San Jose, CA with a presence ... Q Analysts is looking for Data Annotation Technicians to support Ground Truth Data Collection ...

Docugami

Machine Learning / Data Scientist

Kirkland, WA · On-site

Docugami is looking for Machine Learning, Data Science and Math PhD researchers to work alongside our world-renowned science and engineering team to create a revolutionary product. We are looking for ...

Amazon

Catalog Specialist, RCX

Bellevue, WA · On-site

Key job responsibilities • Work closely with our product, technology, and science teams to support Machine Learning (ML) models • Perform data annotation required to train and evaluate ML models ...

Amazon

Catalog Specialist, RCX

Bellevue, WA · On-site

Key job responsibilities • Work closely with our product, technology, and science teams to support Machine Learning (ML) models • Perform data annotation required to train and evaluate ML models ...

Amazon

Catalog Specialist, RCX

Bellevue, WA · On-site

... Machine Learning (ML) models Perform data annotation required to train and evaluate ML models effectively Support data scientists in the development of classification algorithms Collaborate with ...

Amazon

Catalog Specialist, RCX

Bellevue, WA

... Machine Learning (ML) models Perform data annotation required to train and evaluate ML models effectively Support data scientists in the development of classification algorithms Collaborate with ...

Amazon

Catalog Specialist, RCX

Bellevue, WA · On-site

... Machine Learning (ML) models Perform data annotation required to train and evaluate ML models effectively Support data scientists in the development of classification algorithms Collaborate with ...

Amazon

Catalog Specialist, RCX

Bellevue, WA · On-site

... Machine Learning (ML) models Perform data annotation required to train and evaluate ML models effectively Support data scientists in the development of classification algorithms Collaborate with ...

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All JobsFull Time Machine Learning Data Annotation JobsFull Time Machine Learning Data Annotation Jobs in Seattle, WA

Full Time Machine Learning Data Annotation information

See Seattle, WA salary details

$42.7K

$139.7K

$223.6K

How much do full time machine learning data annotation jobs pay per year?

As of Jul 1, 2026, the average yearly pay for full time machine learning data annotation in Seattle, WA is $139,680.00, according to ZipRecruiter salary data. Most workers in this role earn between $112,100.00 and $154,800.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Full Time Machine Learning Data Annotation Specialist, and why are they important?

To thrive as a Full Time Machine Learning Data Annotation Specialist, you need strong attention to detail, basic data literacy, and familiarity with data labeling concepts, often supported by a high school diploma or equivalent. Proficiency in specialized annotation platforms, spreadsheet tools, and sometimes knowledge of Python or labeling frameworks is typically required. Reliability, patience, and effective communication are valuable soft skills for ensuring accuracy and collaborating with team members. These skills and qualities are crucial because they directly impact the quality of training data, which is essential for developing effective machine learning models.

What are Full Time Machine Learning Data Annotation jobs?

Full time machine learning data annotation jobs involve labeling, tagging, or categorizing data such as images, text, audio, or video to help train machine learning models. Data annotators play a crucial role in ensuring that AI systems learn from high-quality, accurately labeled datasets. These positions often require attention to detail, consistency, and sometimes familiarity with the subject matter or specialized tools. Full-time roles may be remote or onsite and can span industries like autonomous vehicles, healthcare, retail, and more.

What are some common challenges faced by machine learning data annotators, and how are these typically addressed within a team?

Machine learning data annotators often encounter challenges such as maintaining consistency in labeling, handling ambiguous data, and meeting tight deadlines for large datasets. Teams usually address these by establishing clear annotation guidelines, conducting regular training sessions, and implementing quality assurance processes like peer reviews and spot checks. Collaboration with data scientists and project managers is also common, ensuring that annotators can ask questions and clarify uncertainties, leading to higher-quality labeled data and a supportive work environment.

What is the difference between Full Time Machine Learning Data Annotation vs Data Labeling Specialist?

AspectFull Time Machine Learning Data AnnotationData Labeling Specialist
CredentialsHigh school diploma or equivalent; some roles prefer technical certificationsHigh school diploma or equivalent; training often provided on the job
Work EnvironmentOffice or remote; collaborative with data science teamsRemote or office; focused on labeling tasks
Industry UsageUsed across AI/ML companies, tech firms, and startupsCommon in AI/ML, data services, and outsourcing companies
Job FocusCreating labeled datasets for machine learning modelsAnnotating data such as images, videos, or text for AI training

Full Time Machine Learning Data Annotation involves creating high-quality labeled datasets for AI models, often requiring technical understanding. Data Labeling Specialists focus on annotating data accurately, typically with less emphasis on technical skills. Both roles are essential in AI development but differ mainly in scope and technical complexity.

What are popular job titles related to Full Time Machine Learning Data Annotation jobs in Seattle, WA? For Full Time Machine Learning Data Annotation jobs in Seattle, WA, the most frequently searched job titles are:
What job categories do people searching Full Time Machine Learning Data Annotation jobs in Seattle, WA look for? The top searched job categories for Full Time Machine Learning Data Annotation jobs in Seattle, WA are:
Full Time Machine Learning Data Annotation jobs near you
Data Annotation Technician

Data Annotation Technician

Q ANALYSTS LLC

Kirkland, WA • On-site, Remote

Full-time

Posted 21 days ago

Job description

Company Description
Join Q Analysts and become part of a world-class organization. Q Analysts has a sixteen-years track record of providing managed services and we've partnered with some of the world's best companies to deliver services that exceed expectations. Q Analysts provides industry-leading managed services that drive Quality for Quality Assurance and Testing of hardware devices, software apps and experiences as well as Ground Truth Data Services for artificial intelligence (AI) and machine learning (ML).
Q Analysts is headquartered in San Jose, CA with a presence throughout the US and internationally. The company has been recognized repeatedly for its industry-leading growth rate and service quality. At Q Analysts, we listen to your needs and help you select what's right for you - this includes the right career opportunities, a choice of comprehensive benefits packages as well as technical training. When you become a Q Analysts employee, you'll see the difference in the superior levels of support and service we deliver to you, our partners, through our Consultant Experience Program. Learn about us here and come join us.
Job Description
Q Analysts is a high growth technology consulting company with a focus on providing Quality Assurance & Testing and Ground Truth Data Services to top technology corporations in the US. We deliver value added services to our clients that include managed services and managed projects.
Q Analysts is looking for Data Annotation Technicians to support Ground Truth Data Collection initiatives and contribute to the development of VR and AR products. The focus of ground truth data collection is to capture various types of data relating to humans, speech and environments to enable quality Artificial Intelligence and Machine Learning algorithms. The Data Annotation Technician will be responsible for analyzing and summarizing data while utilizing specialized tooling for processing. The ideal candidate will have an appreciation for technology, be able to work autonomously and efficiently and have strong attention to detail. This is a short term project with potential for long term.
Responsibilities:
  • Generate answer summaries to a given question from pre-determined content
  • Analyze content and use best judgement for proper answers
  • Meet daily, weekly and monthly velocity expectations
  • Generate daily reports on completed tasks
  • Assist with peer to peer training

Qualifications
Skills and Requirements:
  • Ability to work on repetitive tasks effectively
  • Strong written grammar skills
  • Professional verbal and written communication
  • Able to make judgement calls based on a set of criteria
  • Able to manage time effectively with minimum oversight
  • Organized and detail oriented
  • Adaptable, reliable and ethical
  • Technology skills including tooling and PC
  • Transcription or tagging skills a major plus

Experience:
  • Experience in a related role
  • Experience in a role requiring usage of a variety of technology tools
  • Experience with Microsoft Office 365 and all its components (SharePoint, Forms, Power Automate, Outlook, Word, Excel)

Verification of COVID 19 vaccination, background check, and ability to work in the United States without requiring sponsorship required for all new hires.
Additional Information
All qualified applicants will receive consideration for employment without regard to race, sex, color, religion, sexual orientation, gender identity, national origin, protected veteran status, or on the basis of disability Q Analysts is an EOE. All your information will be kept confidential according to EEO guidelines.

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