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Annotation Jobs in Washington (NOW HIRING)

CaseGuard

Data Annotation Specialist

Arlington, VA

$40K - $50K/yr

Follow detailed annotation and redaction standards to ensure consistency. * Conduct quality checks to identify errors or inconsistencies. * Handle sensitive data with discretion and comply with ...

CaseGuard

Data Annotation Specialist

Arlington, VA · On-site

$40K - $50K/yr

Follow detailed annotation and redaction standards to ensure consistency. * Conduct quality checks to identify errors or inconsistencies. * Handle sensitive data with discretion and comply with ...

Innodata Inc.

AI Solutions Engineer

Washington, DC

$75 - $80/hr

You'll partner with the Solution Architect and Data/Annotation Engineer to turn raw corpora into high-quality, model-ready data. This role suits an engineer who's fluent across modern AI tooling and ...

Innodata Inc.

QA / Evaluation Lead

Washington, DC · On-site

$45 - $50/hr

Design and implement confidence-threshold escalation routing from automated annotation to senior-annotator adjudication * Validate quality scoring and IAA computation within the Innodata data layer

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Annotation information

What is an Annotation job?

An annotation job involves labeling or tagging data, such as text, images, audio, or video, to help train artificial intelligence and machine learning models. Annotators manually or semi-automatically add metadata, such as identifying objects in images, transcribing speech, or categorizing text. This process improves AI accuracy by providing high-quality training data. Annotation work is crucial for industries like autonomous driving, healthcare, and natural language processing.

What does an annotation job do?

An annotation job involves labeling or tagging data, such as images, text, or videos, to help train machine learning models. Workers typically use specialized tools to add accurate annotations, which are essential for developing AI systems in fields like computer vision and natural language processing.

Which 5 jobs will survive AI?

Annotation jobs, which involve labeling data for machine learning, are likely to persist as they require human judgment and domain expertise. Roles such as data annotators, quality assurance specialists, and domain-specific annotators will continue to be essential, especially in areas needing nuanced understanding and accuracy. Skills in critical thinking and familiarity with annotation tools will support job stability in this field.

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

Excelling in an Annotation role generally requires keen attention to detail, strong analytical abilities, and a high level of accuracy, often backed by a relevant educational background. Familiarity with annotation tools, data labeling software, and sometimes basic programming or data management platforms is valuable. Effective time management, consistency, and clear communication are soft skills that differentiate top performers. These competencies are crucial to ensuring data quality and supporting the development of machine learning and AI systems.

How much do annotators make?

Annotators typically earn between $10 and $20 per hour, depending on the complexity of the task, experience, and the employer. Many work remotely and may be paid per task or project rather than hourly, with some platforms offering bonuses for high accuracy or speed.

Is data annotation real or fake?

Data annotation is a legitimate job that involves labeling data such as images, text, or videos to train machine learning models. It requires attention to detail and familiarity with annotation tools, and it is widely used in AI development across various industries.

What are the typical projects or tasks an Annotation specialist works on throughout the week?

Annotation specialists typically work on projects involving the labeling and categorizing of data—such as images, videos, audio, or text—to train machine learning models. Weekly tasks may include reviewing raw data, applying specific tagging guidelines, performing quality checks on completed annotations, and collaborating with team members or machine learning engineers to ensure accuracy and consistency. Frequent feedback sessions and ongoing updates to annotation instructions are common as project requirements evolve. This role often requires close teamwork and clear communication within a collaborative environment, especially for large-scale or rapidly changing projects.

What are the most commonly searched types of Annotation jobs in Washington? The most popular types of Annotation jobs in Washington are:
What are popular job titles related to Annotation jobs in Washington? For Annotation jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Annotation jobs in Washington look for? The top searched job categories for Annotation jobs in Washington are:
What cities in Washington are hiring for Annotation jobs? Cities in Washington with the most Annotation job openings:
Annotation jobs near you
Infographic showing various Annotation job openings in Washington as of July 2026, with employment types broken down into 1% As Needed, 51% Full Time, 45% Part Time, and 3% Contract. Highlights an 56% Physical, 1% Hybrid, and 43% Remote job distribution.
Data & Annotation Engineer

Data & Annotation Engineer

Innodata Inc.

Washington, DC

$55 - $60/hr

Other

Posted 17 days ago

Innodata rating

7.5

Company rating: 7.5 out of 10

Based on 6 frontline employees who took The Breakroom Quiz

162nd of 245 rated software companies

Job description

About the Program: 

Innodata's Federal Practice builds the trusted data layer for critical infrastructure Trust & Safety work. Partnering with a leading systems integrator, we're delivering a modern, governed data services platform in a secure federal (IL4) environment. Over an intensive 20-week phase, you'll help stand up a data services storefront, a DataCard governance framework, synthetic data integration, and Databricks write-back capabilities.

About the Role: 

As the Data/Annotation Engineer, you'll be hands-on with the data itself. You'll administer the annotation toolchain, manage annotation workflows across the corpus, and produce the per-dataset documentation that feeds our governance framework. You'll work with the AI Solutions Engineer to ensure the data going into our models is accurate, well-labeled, and fully traceable. This role is for someone detail-obsessed who understands that great AI starts with disciplined, well-governed data.

Key Responsibilities:

  • 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

Must-Have Qualifications:

  • 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

Nice-to-Have Qualifications:

  • Bachelor's degree in Computer Science, Machine Learning, Data Science, or related field required; Master's degree preferred. Equivalent experience may substitute for degree on a 2-for-1 basis
  • CVAT annotation platform - AI feature configuration and operation
  • DoD or IC data program experience: CUI, distribution statements, federal data governance
  • Evaluation design for AI/ML training data: IAA methodology, drift detection, model performance measurement
  • Video understanding or FMV annotation experience
  • DataCard or ML data provenance framework familiarity

The expected hourly salary range for this position is $55 to $60 p/hour, based on experience, skills, and qualifications.

Note to Candidates: 

Phase D corpus production (Weeks 17-19) is the core demonstration deliverable. Candidates must be genuinely comfortable operating CVAT at production quality against a mission dataset under a milestone deadline

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