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Data Annotation Tech information

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$13

$26

$39

How much do data annotation tech jobs pay per hour?

As of Jun 9, 2026, the average hourly pay for data annotation tech in Seattle, WA is $26.01, according to ZipRecruiter salary data. Most workers in this role earn between $19.18 and $30.91 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Data Annotation Tech position, and why are they important?

To thrive as a Data Annotation Tech, you need keen attention to detail, basic computer literacy, and familiarity with data labeling standards, often supported by a high school diploma or equivalent. Experience with annotation platforms, image or text labeling tools, and basic knowledge of data management systems is highly valuable. Strong organizational skills, patience, and effective communication set top candidates apart in this field. These skills and qualities ensure annotated data is accurate, consistent, and valuable for machine learning or AI projects.

What does a typical day look like for a Data Annotation Tech?

A typical day as a Data Annotation Tech involves reviewing large sets of data—such as images, text, or audio—and accurately labeling or categorizing them using specialized software. You may work independently or as part of a team, following specific project guidelines to ensure data integrity and consistency. Collaboration with project managers or data scientists is common when clarifying ambiguous data points or addressing annotation challenges. Additionally, productivity targets and quality checks are a regular part of the workflow, helping to keep projects on schedule and maintain high standards.

What is a Data Annotation Tech job?

A Data Annotation Tech is responsible for labeling and categorizing data, such as text, images, audio, or video, to train machine learning models. They follow specific guidelines to ensure accuracy and consistency in annotations, which helps improve the performance of AI systems. This role often involves repetitive tasks, attention to detail, and familiarity with various annotation tools. Data annotation is crucial for AI development in industries like healthcare, finance, and autonomous driving.

Is data annotation legit or not?

Data annotation is a legitimate job that involves labeling data such as images, text, or audio to train machine learning models. It is commonly performed remotely and requires attention to detail, basic technical skills, and familiarity with annotation tools. Many companies hire data annotators as part of AI development projects, making it a valid employment option.
What are the most commonly searched types of Data Annotation Tech jobs in Seattle, WA? The most popular types of Data Annotation Tech jobs in Seattle, WA are:
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What cities near Seattle, WA are hiring for Data Annotation Tech jobs? Cities near Seattle, WA with the most Data Annotation Tech job openings:
Data Annotation Tech jobs near you
Infographic showing various Data Annotation Tech job openings in Seattle, WA as of May 2026, with employment types broken down into 50% Full Time, 17% Part Time, and 33% Contract. Highlights an 50% In-person, and 50% Remote job distribution, with an average salary of $54,101 per year, or $26 per hour.
Project Perseus | Speech & Voice AI Analyst - Portuguese (Portugal) Speakers

Project Perseus | Speech & Voice AI Analyst - Portuguese (Portugal) Speakers

Welo Data

Seattle, WA • On-site

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Job Summary:
Welo Data is looking for detail-oriented and reliable individuals to join their team as Speech & Voice AI Analysts. This role focuses on executing high-volume data labeling and annotation tasks across speech and voice datasets to support AI systems.
Responsibilities:
• Execute high-volume data labeling and annotation tasks across speech and voice datasets
• Follow detailed guidelines to ensure consistency, accuracy, and data integrity at scale
• Work with audio and language data, including transcription, categorization, and tagging
• Maintain strong throughput while meeting quality expectations
• Escalate unclear or ambiguous cases appropriately
• Adapt to evolving guidelines and workflows as systems and requirements change
• Support baseline data production needs for AI training pipelines
• Contribute to team calibrations and quality alignment sessions
Qualifications:
Required:
• Native-level fluency in Portuguese (Portugal)
• Strong written communication skills and language fundamentals
• 1 year of work experience in data labeling, annotation, or content-focused work; or a Bachelor's degree or equivalent academic qualification in a related field.
• Ability to follow detailed instructions and apply guidelines consistently
• High attention to detail and ability to maintain accuracy in repetitive tasks
• Comfort working in structured, process-driven environments
• Ability to manage time effectively and maintain steady output
• Willingness to ask questions and escalate when needed
Preferred:
• Basic familiarity with AI, speech technology, or language data is a plus
Company:
With 27+ years of experience, Welo Data is the human-centered infrastructure for globally effective AI. Founded in , the company is headquartered in , , with a team of 1001-5000 employees. The company is currently Late Stage.

Working at Welo Data

What to expect from working at Welo Data

From Welo Data

About Welo Data, in their own words

From Welo Data

Welo Data is a global AI data services company powering the next generation of AI. We build, annotate, and validate the training datasets that make AI models accurate, safe, and ready for the real world — across languages, cultures, and domains.

Our team of experts spans the globe, combining deep technical knowledge with a human-centered approach. If you want your work to shape how AI understands the world, you'll find your place here.

Diversity and inclusion statement

From Welo Data

Our Strength is derived from Winning Together. Welo Data is unequivocally committed to developing and fostering a workplace and organizational culture that values the diversity of thought and perspective delivered by a diverse global workforce operating within an inclusive organization.

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