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Data Labelling Jobs in Seattle, WA (NOW HIRING)

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Data Labelling information

See Seattle, WA salary details

$52.3K

$187.8K

$277.1K

How much do data labelling jobs pay per year?

As of Jun 9, 2026, the average yearly pay for data labelling in Seattle, WA is $187,795.00, according to ZipRecruiter salary data. Most workers in this role earn between $151,900.00 and $193,500.00 per year, depending on experience, location, and employer.

What is a Data Labelling job?

A Data Labelling job involves annotating data, such as text, images, audio, or video, to help train machine learning models. Labelers categorize or tag data by following specific guidelines to ensure accuracy and consistency. This process is essential for improving AI applications, including image recognition, natural language processing, and autonomous systems. Attention to detail and adherence to instructions are key skills required for this role.

What are the typical daily responsibilities of a Data Labelling professional?

Data Labelling professionals are generally responsible for reviewing and accurately annotating large volumes of data—such as images, audio, video, or text—to support machine learning and AI projects. This often involves using specialized labeling platforms and following detailed guidelines provided by data scientists or project managers. You may also participate in regular team meetings to discuss quality standards or address ambiguities in data, and your work is typically reviewed for accuracy before being integrated into training datasets. Collaborating with other data annotators, engineers, and analysts is a common part of the process to ensure consistency and high-quality results.

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

To thrive as a Data Labelling professional, you need strong attention to detail, proficiency with data annotation processes, and a basic understanding of machine learning concepts. Familiarity with annotation tools like Labelbox, Supervisely, or Amazon SageMaker Ground Truth is often required, and some roles may value certifications in data processing or AI fundamentals. Reliability, patience, and the ability to follow precise instructions are important soft skills for success in this position. These skills ensure accurate and consistent data labeling, which is critical for developing effective AI models and maintaining data integrity.

What are the most commonly searched types of Data Labelling jobs in Seattle, WA? The most popular types of Data Labelling jobs in Seattle, WA are:
What are popular job titles related to Data Labelling jobs in Seattle, WA? For Data Labelling jobs in Seattle, WA, the most frequently searched job titles are:
What job categories do people searching Data Labelling jobs in Seattle, WA look for? The top searched job categories for Data Labelling jobs in Seattle, WA are:
What cities near Seattle, WA are hiring for Data Labelling jobs? Cities near Seattle, WA with the most Data Labelling job openings:
Data Labelling jobs near you
Infographic showing various Data Labelling job openings in Seattle, WA as of May 2026, with employment types broken down into 2% Internship, 74% Full Time, 14% Part Time, and 10% Contract. Highlights an 93% In-person, 2% Hybrid, and 5% Remote job distribution, with an average salary of $187,795 per year, or $90.3 per hour.
Turkish Data Labeling Analyst(Speech & Voice)

Turkish Data Labeling Analyst(Speech & Voice)

Welo Data

Seattle, WA • On-site

Full-time

Posted 7 days ago

Job description

Job Summary:
Welo Data is looking for detail-oriented and reliable individuals to join our team as Data Labeling Analysts, supporting speech and voice AI systems. This role focuses on building datasets for AI systems through high-volume data labeling and annotation tasks.
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 Croatian
• 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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