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Overnight Ai Data Labeling information

What is the difference between Overnight Ai Data Labeling vs Data Annotation Specialist?

AspectOvernight Ai Data LabelingData Annotation Specialist
CredentialsBasic computer skills, attention to detailSimilar, often requires familiarity with annotation tools
Work EnvironmentRemote or flexible hours, often project-basedOffice or remote, depending on employer
Industry UsageCommon in AI and machine learning projectsUsed across AI, healthcare, autonomous vehicles
Search IntentFocus on overnight or flexible schedulingBroader annotation roles, less emphasis on timing

Overnight Ai Data Labeling typically involves quick turnaround tasks with flexible hours, often performed remotely. Data Annotation Specialists may have similar skills but usually work regular hours and may handle more complex annotation tasks. Both roles are essential in AI development, but Overnight Ai Data Labeling emphasizes speed and flexibility, whereas Data Annotation Specialists focus on detailed, accurate labeling across various industries.

What are the key skills and qualifications needed to thrive as an Overnight AI Data Labeler, and why are they important?

To thrive as an Overnight AI Data Labeler, you need strong attention to detail, accuracy, and the ability to follow complex instructions, often supported by a high school diploma or relevant experience. Familiarity with data labeling platforms, annotation tools, and basic computer applications is typically required. Strong time management, self-motivation, and dependable communication are essential soft skills for working independently during overnight shifts. These skills ensure high-quality, consistent data annotation that directly impacts the performance and reliability of AI models.

What is overnight AI data labeling?

Overnight AI data labeling involves annotating and categorizing data, such as images, videos, or text, during nighttime hours to prepare it for use in training artificial intelligence models. This work typically requires attention to detail and accuracy, as the quality of labeled data directly affects AI performance. Overnight shifts are often used by companies to ensure a continuous workflow and to accelerate project timelines. Data labelers may use specialized tools to tag, classify, or segment data according to specific guidelines provided by clients or employers.

What are some common challenges faced by overnight AI data labeling professionals, and how can they be addressed?

Overnight AI data labeling professionals often face challenges such as maintaining focus during late hours, managing screen fatigue, and adapting to fast-paced project requirements. To address these, it's important to establish a consistent sleep schedule, take regular short breaks to rest your eyes, and stay organized by tracking progress against nightly goals. Collaborating with teammates through scheduled check-ins or chat platforms can also help maintain motivation and ensure high-quality results, even during less traditional work hours.
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Overnight Ai Data Labeling jobs near you
Infographic showing various Overnight Ai Data Labeling job openings in the United States as of June 2026, with employment types broken down into 90% Full Time, and 10% Part Time. Highlights an 100% In-person job distribution.
Arabic Data Labeling Analyst(Speech & Voice)

Arabic Data Labeling Analyst(Speech & Voice)

Welocalize

Seattle, WA

$26 - $28/hr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 13 days ago

Welocalize rating

5.9

Company rating: 5.9 out of 10

Based on 10 frontline employees who took The Breakroom Quiz

335th of 427 rated business services

Job description

Overview

Welo Data is looking for detail-oriented and reliable individuals to join our team as Data Labeling Analysts, supporting speech and voice AI systems.

This is a high-impact production role focused on building the datasets that power real-world AI systems. You’ll be working with audio, speech, and language data — helping ensure models are trained on accurate, well-structured, and representative inputs.

While this role is more execution-focused than evaluation-heavy roles, it still requires strong judgment, attention to detail, and consistency. The work sits at the intersection of language, data, and AI systems — where precision and discipline matter at scale.

We’re looking for people who are dependable, focused, and take pride in producing high-quality work, even across repetitive workflows.

Project Details
  • Job Title: Data Labeling Analyst
  • Hiring in: Onsite (Bay Area, Seattle, NYC, or client-dependent)
  • Hours: Full-time, 40 hours per week
  • Employment Type: W2 Full-Time Employee
  • Work Authorization: Must be authorized to work in the U.S. (no visa sponsorship)
  • Pay Rate: $26 - $28/hour

Important: This is a 100% onsite position — remote work is not available for this role. To be considered, candidates must be located in or able to commute to one of the following cities: New York City, Seattle, Bellevue, Redmond, San Francisco, Sunnyvale, or Burlingame. Please only apply if you meet this location requirement.

What You'll Do
  • Execute high-volume data labeling and annotation tasks across speech and voice datasets
  • Follow detailed guidelines to ensure consistency, accuracy, and data integrity at scale
  • Work with audio and language data, including transcription, categorization, and tagging
  • Maintain strong throughput while meeting quality expectations
  • Escalate unclear or ambiguous cases appropriately
  • Adapt to evolving guidelines and workflows as systems and requirements change
  • Support baseline data production needs for AI training pipelines
  • Contribute to team calibrations and quality alignment sessions
What We're Looking For
  • Native-level fluency in Croatian
  • Strong written communication skills and language fundamentals
  • 1 year of work experience in data labeling, annotation, or content-focused work; or a Bachelor's degree or equivalent academic qualification in a related field.
  • Ability to follow detailed instructions and apply guidelines consistently
  • High attention to detail and ability to maintain accuracy in repetitive tasks
  • Comfort working in structured, process-driven environments
  • Ability to manage time effectively and maintain steady output
  • Willingness to ask questions and escalate when needed
  • Basic familiarity with AI, speech technology, or language data is a plus
Benefits
  • Paid Vacation: 6 days
  • Paid Company Holidays: 2 days (Memorial Day and Labor Day)
  • Paid Sick Leave: accrued per applicable state law and company policy
  • Medical, Dental, and Vision Insurance (eligibility applies)
  • Health Savings Account (HSA)
  • 401(k) Retirement Plan
  • Employee Assistance Program
  • Additional voluntary benefits (life, accident, critical illness, etc.)

Onsite Perks (where applicable):
Free breakfast, lunch, and dinner
Stocked micro-kitchens with snacks and beverages
Commuter benefits, including shuttles and bike-to-work options
Unique campus features depending on location

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