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Remote Entry Level Data Annotation Jobs in Everett, WA

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Remote Entry Level Data Annotation information

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$12

$22

$34

How much do remote entry level data annotation jobs pay per hour?

As of Jun 27, 2026, the average hourly pay for remote entry level data annotation in Everett, WA is $22.36, according to ZipRecruiter salary data. Most workers in this role earn between $18.08 and $24.18 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Remote Entry Level Data Annotation specialist, and why are they important?

To thrive as a Remote Entry Level Data Annotation specialist, you need strong attention to detail, basic computer literacy, and a high school diploma or equivalent. Familiarity with annotation platforms, data labeling tools, and sometimes basic spreadsheet software is typically required. Effective time management, communication, and the ability to follow precise instructions help candidates excel in this role. These skills ensure accurate, high-quality data labeling, which is crucial for training reliable machine learning models.

What is the difference between Remote Entry Level Data Annotation vs Remote Data Labeling Specialist?

AspectRemote Entry Level Data AnnotationRemote Data Labeling Specialist
CredentialsBasic computer skills, attention to detailSimilar, often no formal certifications required
Work EnvironmentRemote, flexible hoursRemote, often part-time or freelance
Industry UsageAI, machine learning, tech companiesAI, autonomous vehicles, tech firms
Search IntentEntry-level data annotation jobsData labeling roles for AI projects

Remote Entry Level Data Annotation and Remote Data Labeling Specialist roles are similar in credentials and work environment, both serving AI and machine learning industries. The main difference lies in terminology used by employers and job seekers, with 'Data Labeling Specialist' often emphasizing more specialized tasks. Both roles are suitable for individuals seeking remote, entry-level positions in data preparation for AI applications.

What are some common challenges faced by remote entry-level data annotators, and how can they be managed?

Remote entry-level data annotators often encounter challenges related to maintaining focus and productivity while working independently, as well as ensuring consistency and accuracy in their annotations. To manage these challenges, it's helpful to establish a clear daily routine, set up a dedicated workspace, and actively communicate with team leads or supervisors for guidance. Utilizing collaboration tools and regularly reviewing project guidelines can also help maintain annotation quality and keep workflow on track.

What is a Remote Entry Level Data Annotation job?

A Remote Entry Level Data Annotation job involves labeling, tagging, or categorizing data such as images, text, audio, or video from a remote location. These roles are crucial for training machine learning algorithms, as annotated data helps improve the accuracy of artificial intelligence models. Entry-level positions typically require attention to detail and basic computer skills but do not usually require prior experience or specialized knowledge. Working remotely allows you to perform these tasks from home or any location with internet access.
What are popular job titles related to Remote Entry Level Data Annotation jobs in Everett, WA? For Remote Entry Level Data Annotation jobs in Everett, WA, the most frequently searched job titles are:
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What cities near Everett, WA are hiring for Remote Entry Level Data Annotation jobs? Cities near Everett, WA with the most Remote Entry Level Data Annotation job openings:
Remote Entry Level Data Annotation jobs near you
Deep Learning Quality Specialist

Deep Learning Quality Specialist

Carbon Robotics

Seattle, WA • On-site, Remote

Other

Posted 7 days ago

Job description

As a Deep Learning Quality Specialist at Carbon Robotics you'll be responsible for maintaining our expanding dataset of high resolution images that feed our computer vision algorithms. You will develop a deep understanding of our data annotation practices and assist in diagnosing & fixing complex deep learning models to ensure our products are robust & reliable. You will help the Deep Learning team by performing field tests and identifying issues with models. You'll do whatever it takes - which includes going to the farm - to ensure our customers have reliable and safe products.

Our office is based in Seattle, WA, but this role can be fully remote. 

What you'll do:

  • Audit data to ensure clean and appropriate datasets
  • Look through imagery and correct labels and classifications then give feedback to labelers
  • Work closely with support to help investigate issues and determine what is needed to insure data integrity
  • Review data irregularities detected by automated tooling
  • Validate solutions, document results and record customer feedback
  • Translates field tests, model issues and analyze customer feedback
  • Prepare cases for field personnel to review labels/predictions
  • Help the Deep Learning team prioritize tasks based on impact to customer satisfaction

Knowledge, Skills, and Abilities for Success:

  • Education or professional experience in agronomy & farming or data annotation
  • Highly motivated, independent thinker with great problem solving skills
  • Highly organized with excellent time management to juggle multiple priorities at the same time
  • Collaboration skills to work with customers and internal teams simultaneously
  • High level of attention to detail & the ability to think strategically
  • Detail-oriented, with proven ability to deliver accurate reporting
  • Intermediate to advanced Google Suite and Confluence skills desired
  • Ability to assess high risk situations & make safe independent decisions on a risk based process
  • Traveling required 10-15%

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