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Flexible Data Annotation Tech Jobs in Seattle, WA

TSMG

Robot Teleoperator (AI & Robotics)

Seattle, WA · On-site

Support data annotation and quality validation activities * Maintain accurate operational records ... Work directly with cutting-edge robotics technology * Gain experience in one of the fastest-growing ...

LVT

Staff Data Engineer

Seattle, WA

$130K - $156K/yr

Our CEO, Ryan Porter, was named an EY Entrepreneur of the Year 2025 , and our CTO, Steve Lindsey ... Labels & Annotation Data Lifecycle: Own how labels and semantic annotations are appended to ...

LVT

Staff Data Engineer

Seattle, WA · On-site

$130K - $156K/yr

Our CEO, Ryan Porter, was named an EY Entrepreneur of the Year 2025, and our CTO, Steve Lindsey ... Labels & Annotation Data Lifecycle: Own how labels and semantic annotations are appended to ...

TSMG

Robot Teleoperator (AI & Robotics)

Seattle, WA · On-site

Support data annotation and quality validation activities * Maintain accurate operational records ... Work directly with cutting-edge robotics technology * Gain experience in one of the fastest-growing ...

Welocalize

Polish Data Labeler

Seattle, WA · On-site

$26 - $28/hr

Execute high-volume data labeling and annotation tasks across speech and voice datasets * Follow ... Basic familiarity with AI, speech technology, or language data is a plus Benefits * Paid Vacation ...

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How much do flexible data annotation tech jobs pay per hour?

As of Sep 5, 2026, the average hourly pay for flexible data annotation tech in Seattle, WA is $26.00, according to ZipRecruiter salary data. Most workers in this role earn between $19.13 and $30.91 per hour, depending on experience, location, and employer.

What is a flexible data annotation tech?

Flexible Data Annotation Tech jobs involve labeling, categorizing, or tagging data—such as images, text, audio, or video—to help train machine learning models. These roles are often remote or offer flexible schedules, making them appealing for those seeking adaptable work hours. Tasks can include identifying objects in photos, transcribing audio, or sorting information based on specific guidelines. The work is essential for improving the accuracy of artificial intelligence systems by providing them with high-quality annotated data. No advanced technical skills are usually required, but attention to detail and reliability are important.

What are the key skills and qualifications needed to thrive as a flexible data annotation tech, and why are they important?

To thrive as a Flexible Data Annotation Tech, you need attention to detail, accuracy, and a basic understanding of data labeling or annotation processes, often requiring at least a high school diploma. Familiarity with annotation platforms, data labeling tools, and productivity software is typically necessary, and experience with machine learning datasets can be advantageous. Strong time management, communication, and adaptability help you excel in collaborative and ever-changing project environments. These skills ensure high-quality, consistent data output that directly impacts the performance of AI and machine learning systems.

What are some common challenges faced by flexible data annotation techs, and how can they be addressed?

Flexible Data Annotation Techs often encounter challenges such as maintaining consistency across large volumes of data, adapting to evolving project guidelines, and managing tight deadlines. To address these challenges, it's important to establish clear communication with project leads, regularly review annotation protocols, and utilize available training resources. Building strong attention to detail and staying organized can also help ensure high-quality outputs and job satisfaction.

What is the difference between Flexible Data Annotation Tech vs Data Labeler?

AspectFlexible Data Annotation TechData Labeler
CredentialsBasic computer skills, training in annotation toolsBasic education, sometimes specific software training
Work EnvironmentRemote or on-site, tech-focusedPrimarily remote or on-site, data processing settings
Industry UsageAI, machine learning, data scienceAI, machine learning, data preparation
Job FocusApplying labels to datasets using annotation toolsLabeling data according to guidelines

Flexible Data Annotation Tech roles involve using specialized tools to annotate datasets for AI training, often requiring some technical training. Data Labelers focus on applying labels to data, typically with less technical complexity. Both roles are essential in AI development but differ mainly in technical requirements and scope.

Can I do data annotation with no experience?

Data annotation roles often do not require prior experience, as training is typically provided to teach specific labeling tools and guidelines. Basic computer skills and attention to detail are usually sufficient to start, making it accessible for beginners. Over time, developing familiarity with annotation software and understanding data types can improve efficiency and accuracy.

Do data annotation jobs offer flexible hours?

Data annotation jobs often offer flexible hours, allowing workers to choose when they complete tasks, especially in freelance or remote roles. However, some positions may have specific deadlines or part-time schedules depending on the employer or platform used. Flexibility can vary based on the company's policies and project requirements.

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:

What are popular job titles related to Flexible Data Annotation Tech jobs in Seattle, WA?

For Flexible Data Annotation Tech jobs in Seattle, WA, the most frequently searched job titles are:

What job categories do people searching Flexible Data Annotation Tech jobs in Seattle, WA look for?

The top searched job categories for Flexible Data Annotation Tech jobs in Seattle, WA are:

Flexible Data Annotation Tech jobs near you

Japanese Language Expert - Remote

YO AI Labs

Seattle, WA • Remote

$65 - $100/hr

Full-time

Posted 12 days ago

Job description

Job Title: Japanese Language Expert

Job Type: Contract
Location: Remote

Job Overview

We are seeking experienced Japanese Language Experts to contribute their linguistic expertise to a project focused on improving next-generation AI systems. In this role, you will work with Japanese and English audio and written content, ensuring accurate transcription, translation, contextual fidelity, and high-quality linguistic output.

No prior AI experience is required—your language expertise, attention to detail, and bilingual proficiency are what matter most.

Key Responsibilities
  • Accurately transcribe audio and written materials between Japanese and English.
  • Review, edit, and proofread transcripts to ensure linguistic accuracy, clarity, and contextual fidelity.
  • Identify and correct grammatical, terminology, and transcription errors.
  • Provide detailed linguistic feedback to improve transcription quality and consistency.
  • Collaborate with remote team members to maintain project quality standards and workflows.
  • Manage multiple transcription and language tasks while meeting project deadlines.
  • Maintain consistent formatting and high-quality deliverables across assignments.
  • Communicate effectively with team members through written and verbal channels.
Required Skills & Qualifications
  • Native or near-native proficiency in Japanese with strong command of English.
  • Demonstrated experience in transcription, translation, localization, or related language services.
  • Excellent written and verbal communication skills in both Japanese and English.
  • Exceptional attention to detail and commitment to transcription accuracy.
  • Ability to work independently while collaborating effectively within a remote team.
  • Proficiency with transcription software, digital tools, and collaboration platforms.
  • Strong organizational, prioritization, and time-management skills.
Preferred Qualifications
  • Prior experience with Japanese-English bilingual transcription projects.
  • Familiarity with technical, business, or industry-specific terminology.
  • Academic or professional background in linguistics, Japanese studies, translation, language studies, or a related field.
  • Experience reviewing or quality-checking language data.
  • Familiarity with AI, language technology, or data annotation projects is a plus.