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Hourly Remote Data Annotation Jobs in Seattle, WA

Actalent

Principal Research Scientist

Everett, WA · Remote

$170K/yr

Hourly pay: $50.00 Location: Remote Employment: Full‑time Data Annotation Intern - Remote Independent contractor opportunity to assist high‑quality AI data creation. Internship Kaizen Summer ...

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Hourly Remote Data Annotation information

What are the key skills and qualifications needed to thrive as an Hourly Remote Data Annotation Specialist, and why are they important?

To excel as an Hourly Remote Data Annotation Specialist, you need strong attention to detail, accuracy, and familiarity with data labeling concepts, often supported by a high school diploma or equivalent. Proficiency with annotation platforms, labeling tools (like Labelbox or Supervisely), and sometimes basic knowledge of spreadsheets or image/video editing software is typically required. Reliability, time management, and clear communication are vital soft skills for succeeding in a remote, deadline-driven environment. These abilities ensure high-quality, consistent annotations that are critical for training AI models and meeting project requirements.

What are some common challenges faced by hourly remote data annotation workers and how can they be addressed?

Hourly remote data annotation workers often encounter challenges such as repetitive tasks, maintaining high accuracy, and managing time effectively without direct supervision. To address these, it's important to establish a structured daily routine, take regular breaks to prevent fatigue, and utilize any quality control guidelines provided by the employer. Staying in regular communication with team leads or project managers can also help clarify any ambiguities and ensure consistent work quality.

What is the difference between Hourly Remote Data Annotation vs Hourly Remote Data Labeling?

AspectHourly Remote Data AnnotationHourly Remote Data Labeling
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote, flexible hoursRemote, flexible hours
Industry UsageCommon in AI/ML projects for training dataCommon in AI/ML projects for training data
Job FocusAdding annotations to data (e.g., bounding boxes, tags)Assigning labels to datasets for model training

Both roles involve working remotely to prepare data for machine learning models. Data annotation typically involves marking specific features within data, while data labeling involves categorizing data into predefined classes. The skills and work environment are similar, making them closely related but distinct tasks within AI data preparation.

What is hourly remote data annotation?

Hourly remote data annotation involves labeling or categorizing data, such as images, text, or audio, for use in machine learning and artificial intelligence projects. Annotators work from home and are usually paid by the hour to review and tag data according to specific guidelines provided by the employer. This work is essential for training algorithms to recognize patterns or interpret information accurately. Data annotation tasks vary and can include image classification, text categorization, or identifying objects within media. It’s a popular entry-level remote job that requires attention to detail and the ability to follow instructions closely.
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Hourly Remote Data Annotation jobs near you
Deep Learning Quality Specialist

Deep Learning Quality Specialist

Carbon Robotics

Seattle, WA • On-site, Remote

Other

Posted 24 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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