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Remote Data Annotation Jobs in Edmonds, WA (NOW HIRING)

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Remote Data Annotation information

How hard is it to get hired by data annotation?

Getting hired for a remote data annotation role typically requires basic computer skills, attention to detail, and sometimes familiarity with annotation tools or platforms. Many positions are entry-level and do not require advanced education, making the application process relatively accessible, though competition can vary based on the employer and job volume.

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

To thrive as a Remote Data Annotation specialist, strong attention to detail, accuracy, and familiarity with basic data processing concepts are essential, often requiring a high school diploma or equivalent. Experience using data labeling platforms, annotation tools (such as Labelbox or Supervisely), and sometimes familiarity with spreadsheet software may be required. Excellent time management, communication skills, and the ability to work independently are valuable soft skills in this remote role. These skills are vital to ensure that data annotations are consistent, precise, and delivered on schedule, which directly impacts the quality of AI and machine learning outcomes.

How to make $1000 a week remote?

Remote data annotation jobs typically pay per task or hour, with earnings varying based on experience, accuracy, and the complexity of the data. To make $1000 a week, you need to work consistently, often requiring 20-40 hours depending on pay rates, which can range from a few cents to several dollars per annotation. Building skills in specific tools and maintaining high accuracy can help increase your earning potential in this field.

What are the typical daily tasks for someone working in Remote Data Annotation?

Daily tasks for a Remote Data Annotation role usually involve reviewing and labeling large volumes of data—such as images, audio clips, text, or video—according to specific project guidelines. You will use specialized annotation tools to identify objects, transcribe content, categorize information, or tag relevant features to support machine learning projects. Communication with project managers or quality assurance teams may be necessary for feedback and clarity on guidelines. Most roles also require regular self-checks for accuracy and the ability to meet productivity quotas or deadlines. This structure allows for a combination of focused individual work and occasional team collaboration to ensure project goals are met.

How can I make 2000 a week working from home?

Remote data annotation jobs can pay between $10 and $20 per hour, so earning $2000 weekly would require working approximately 100 to 200 hours. Increasing income may involve taking on multiple projects, improving accuracy to access higher-paying tasks, or gaining specialized skills in areas like medical or AI data annotation. Consistent work and efficient time management are essential to reach this income level.

What is a Remote Data Annotation job?

A Remote Data Annotation job involves labeling, tagging, or categorizing data (such as images, text, audio, or video) to help improve machine learning models. This work is typically done from home using specialized annotation tools provided by employers. Accuracy and attention to detail are essential, as the quality of annotations directly impacts AI model performance. Many companies hire remote annotators on a freelance, part-time, or contractual basis.

Does data annotation actually pay?

Data annotation jobs typically pay hourly or per task rates, with compensation varying based on complexity and platform. Many remote data annotation roles offer competitive pay, especially for experienced annotators using tools like labeling software, and some positions provide consistent income. However, pay rates can differ widely across companies and projects, so it is important to research specific opportunities.
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Remote Data Annotation jobs near you
Infographic showing various Remote Data Annotation job openings in Edmonds, WA as of July 2026, with employment types broken down into 40% Full Time, 20% Part Time, and 40% Contract. Highlights an 100% Remote job distribution.
Deep Learning Quality Specialist

Deep Learning Quality Specialist

Carbon Robotics

Seattle, WA • On-site, Remote

Other

Posted 21 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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