ZipRecruiter

Log In

2

Data Labeler Remote Jobs in Renton, WA (NOW HIRING)

YO AI Labs

Video Annotation Expert - Remote

Seattle, WA · Remote

$50 - $90/hr

Contractor Location: Remote Role Overview We are looking for detail-oriented Video Annotation ... The role involves accurate video labeling and structured data annotation to support AI and machine ...

New

YO AI Labs

Video Annotation Expert - Remote

Seattle, WA · Remote

$50 - $90/hr

Contractor Location: Remote Role Overview We are looking for detail-oriented Video Annotation ... The role involves accurate video labeling and structured data annotation to support AI and machine ...

New

widenet

Sr. AI Security Engineer

Seattle, WA · On-site +1

$85 - $95/hr

Potential opening for remote candidates in PST. This position will support AI workloads across our ... the same data controls as other egress paths - Establish security requirements for RAG ...

All JobsData Labeler JobsData Labeler Remote JobsData Labeler Remote Jobs in Renton, WA

Data Labeler Remote information

See Renton, WA salary details

$16

$43

$64

How much do data labeler remote jobs pay per hour?

As of Sep 14, 2026, the average hourly pay for data labeler remote in Renton, WA is $43.51, according to ZipRecruiter salary data. Most workers in this role earn between $38.12 and $49.23 per hour, depending on experience, location, and employer.

What does a remote data labeler do?

A remote data labeler is responsible for annotating or tagging data—such as images, videos, audio, or text—from a remote location, typically working from home. Their work helps train machine learning models by providing accurate, labeled datasets that algorithms use to learn and make predictions. Data labelers follow specific guidelines to ensure consistency and accuracy, and may use specialized software tools to complete their tasks. This role is essential in industries like artificial intelligence, self-driving cars, and natural language processing. Remote data labelers often work as freelancers or as part of distributed teams for tech companies.

What are the key skills and qualifications needed to thrive as a remote data labeler?

To thrive as a Data Labeler Remote, you need strong attention to detail, basic data analysis skills, and familiarity with data annotation processes, often supported by a high school diploma or equivalent. Proficiency with labeling platforms, annotation tools, and sometimes knowledge of spreadsheet software are typically required. Reliability, time management, and effective communication are crucial soft skills for maintaining accuracy and meeting project deadlines in a remote setting. These skills ensure high-quality, consistent labeled data, which is essential for training reliable machine learning models.

What are some common challenges faced by remote data labelers and how can they be managed?

Remote data labelers often encounter challenges such as maintaining focus during repetitive tasks, ensuring consistent annotation quality, and communicating effectively with distributed teams. To manage these, it's helpful to establish a structured work routine, take regular breaks to prevent fatigue, and use annotation guidelines provided by employers. Leveraging collaboration tools for feedback and clarification also helps maintain high-quality output and fosters a sense of connection with team members.

What is the difference between Data Labeler Remote vs Data Annotator Remote?

AspectData Labeler RemoteData Annotator Remote
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote, flexible hoursRemote, flexible hours
Industry UsageCommon in AI/ML data preparationCommon in AI/ML data preparation
Job FocusLabeling data points for machine learningAnnotating data for training AI models

Both Data Labeler Remote and Data Annotator Remote roles involve preparing data for AI and machine learning projects. While the terms are often used interchangeably, Data Labeler Remote typically emphasizes labeling data points, whereas Data Annotator Remote may include more detailed annotation tasks. Both roles require similar skills and are performed remotely, making them accessible for individuals seeking flexible data-related jobs.

How much does a data labeler remote make?

Remote data labelers typically earn between $12 and $20 per hour, depending on experience, complexity of tasks, and the company. Some positions may offer additional incentives or flexible schedules, but wages generally align with entry-level data annotation roles in the industry.

Is data labeling a good career?

Data labeling is a common entry-level role in the AI and machine learning industry, involving annotating data such as images, text, or audio to train algorithms. It often offers flexible remote work options and requires attention to detail but typically has lower barriers to entry and limited career advancement without additional skills or certifications.

What job categories do people searching Data Labeler Remote jobs in Renton, WA look for?

The top searched job categories for Data Labeler Remote jobs in Renton, WA are:

What cities near Renton, WA are hiring for Data Labeler Remote jobs?

Cities near Renton, WA with the most Data Labeler Remote job openings:

Data Labeler Remote jobs near you

Video Annotation Expert - Remote

Seattle, WA • Remote

YO AI Labs
See more jobs at YO AI Labsexternal

$50 - $90/hr

Full-time

Posted 3 days ago

New

Job description

Video Annotation Specialist

Job Type: Contractor
Location: Remote

Role Overview

We are looking for detail-oriented Video Annotation Specialists to review and annotate videos of robotic arms performing various tasks. The role involves accurate video labeling and structured data annotation to support AI and machine-learning projects.

Key Responsibilities
  • Review videos and identify key actions, events, and outcomes.
  • Annotate and label video content according to project guidelines.
  • Use video annotation tools to create accurate, structured datasets.
  • Maintain consistency and accuracy across annotations.
  • Collaborate with team members to resolve unclear cases.
  • Participate in quality checks and incorporate feedback.
Requirements
  • Experience in video annotation, data labeling, or similar work preferred.
  • Strong attention to detail and accuracy.
  • Familiarity with video annotation tools.
  • Good written communication and collaboration skills.
  • Strong time-management and organizational abilities.
  • Experience with AI, machine learning, or robotics projects is a plus.