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Day Data Annotation Jobs (NOW HIRING)

Innodata Inc.

Data & Annotation Engineer

Washington, DC · On-site

$55 - $60/hr

As the Data/Annotation Engineer, you'll be hands-on with the data itself. You'll administer the ... CVAT - deployment and day-to-day operation required; this is not a nice-to-have * Annotated dataset ...

Innodata Inc.

$55 - $60/hr

As the Data/Annotation Engineer, you'll be hands-on with the data itself. You'll administer the ... CVAT - deployment and day-to-day operation required; this is not a nice-to-have * Annotated dataset ...

Teleskope

Jr. AI Engineer - Data Annotation

New York, NY · On-site

$75K - $90K/yr

This is a hybrid role requiring 3+ days in-office in New York City. Who Should Apply We're looking ... What You'll Do * Do hands-on data annotation and quality control (labeling, reviewing, and ...

Encord

Human Data Operations Strategist

New York, NY · On-site

Oversee data annotation projects, translating complex AI and machine learning requirements into ... Strong in-person culture: 4 days/week * Flexible PTO to fully recharge * Annual learning ...

Encord

Strategic Projects Lead

New York, NY · On-site

Own data annotation projects end-to-end, translating complex AI/ML requirements into clear ... Strong in-person culture: 4 days/week * Flexible PTO to fully recharge * Annual learning ...

Encord

Strategic Projects Lead

San Francisco, CA · On-site

Own data annotation projects end-to-end, translating complex AI/ML requirements into clear ... Strong in-person culture: 4 days/week * Flexible PTO to fully recharge * Annual learning ...

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Day Data Annotation information

What is a day data annotation job?

Day Data Annotation jobs involve reviewing and tagging data, such as images, text, audio, or video, during regular daytime hours. Annotators help prepare datasets for machine learning and artificial intelligence by labeling or categorizing information according to specific guidelines. This work is essential for training algorithms to recognize patterns, objects, or language. Day Data Annotation can be done remotely or in-office, and it often requires attention to detail and good communication skills.

What are the key skills and qualifications needed to thrive as a day data annotation specialist?

To excel as a Day Data Annotation Specialist, you need strong attention to detail, data entry accuracy, and a solid understanding of the subject matter being annotated, often supported by a high school diploma or relevant experience. Familiarity with annotation tools, spreadsheets, and data management software is typically required. Excellent concentration, time management, and clear communication skills help professionals stand out in this role. These abilities are crucial to ensure high-quality, consistent data labeling that directly impacts the performance of machine learning models and downstream business applications.

What are some common challenges faced by day data annotation specialists and how can they be addressed?

Day Data Annotation specialists often encounter challenges such as maintaining high accuracy while handling repetitive tasks, interpreting ambiguous data, and meeting tight deadlines. To address these, it's important to develop strong attention to detail, use project guidelines as references, and communicate with team leads or peers when uncertainties arise. Many organizations also provide regular feedback and quality assurance checks, which help annotators improve their performance and consistency over time.

What is the difference between Day Data Annotation vs Data Labeler?

AspectDay Data AnnotationData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or on-site, collaborative teamsRemote or on-site, independent work
Industry UsageAI/ML companies, tech firmsAI/ML, data processing companies
Job FocusAnnotating data for machine learning modelsLabeling data to train AI systems

Day Data Annotation and Data Labeler roles are similar, focusing on preparing data for AI. Day Data Annotation often involves more detailed annotation tasks, while Data Labelers may perform broader labeling activities. Both roles require basic technical skills and are vital in AI development across tech industries.

Can I do data annotation with no experience?

Day data annotation jobs often do not require prior experience, as training is typically provided to teach you how to label data accurately. Basic computer skills and attention to detail are usually sufficient to start, and some roles may require familiarity with annotation tools or platforms. Entry-level positions are common and can serve as a stepping stone to more advanced data-related roles.

What cities are hiring for Day Data Annotation jobs?

Cities with the most Day Data Annotation job openings:

What are the most commonly searched types of Data Annotation jobs?

The most popular types of Data Annotation jobs are:

What states have the most Day Data Annotation jobs?

States with the most job openings for Day Data Annotation jobs include:

Day Data Annotation jobs near you
Infographic showing various Day Data Annotation job openings in the United States as of June 2026, with employment types broken down into 1% As Needed, 60% Full Time, 36% Part Time, 2% Contract, and 1% Nights. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Data Annotation Engineer

Jobtailor

Washington, DC • On-site

$120 - $180/hr

Other

Posted 8 days ago

Job description

  • Receive, validate, ingest, and ontology-map the ODIN mission-aligned corpus from AFS delivery
  • Produce the ODIN load report: corpus description, ontology mapping, readiness state
  • Configure CVAT annotation pipeline against the Phase 1 starter kit rule pack
  • Operate both self-service and lightweight white-glove annotation paths during Phase D corpus production
  • Produce 50-100 label demonstration corpus across synthetic and mission-aligned content
  • Support QA/Evaluation Lead on QC execution and corpus annotation dry-runs
  • Associate DataCard provenance records with annotated and synthetic outputs in coordination with the Solution Architect.
Requirements
  • Bachelor's degree in Data Science, Computer Science, or related field preferred. Equivalent experience may substitute for degree on a 2-for-1 basis.
  • 5+ years total professional experience, 3+ years in data engineering or annotation operations
  • CVAT - deployment and day-to-day operation required; this is not a nice-to-have
  • Annotated dataset ingest pipelines: schema mapping, format validation, ontology alignment
  • Full-motion video (FMV) annotation concepts and tooling
  • Python scripting for data wrangling, validation, and format conversion
  • Active Secret clearance with TS/SCI eligibility.
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