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Data Annotation Engineer Jobs in Washington (NOW HIRING)

Jobtailor

Data Annotation Engineer

Washington, DC · On-site

$120 - $180/hr

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 ...

Innodata Inc.

AI Solutions Engineer

Washington, DC · On-site

$75 - $80/hr

You'll integrate synthetic data generation into the pipeline, stand up and tune the annotation ... This role suits an engineer who's fluent across modern AI tooling and enjoys making sophisticated ...

Jobtailor

Technical Project Manager

Washington, DC · On-site

$120 - $150/hr

Administer CVAT + SAM 2 toolchain in coordination with the Data & Annotation Engineer * Facilitate standups, working sessions, and phase gate preparation * Coordinate Technical Writer onboarding and ...

YO AI Labs

AI Data Science Expert - Remote

Washington, DC · Remote

$100 - $200/hr

Prompt Engineering * AI Output Evaluation * Quality Assurance * Technical Documentation * Technical & Report Writing * Content Review & Editing * Data Annotation * Data Interpretation * Fact Checking

YO AI Labs

AI Finance Expert - Remote

Washington, DC · Remote

$100 - $200/hr

Prompt Engineering * AI Output Evaluation * Financial Analysis * Technical & Report Writing * Business Communication * Content Review & Editing * Fact Checking * Data Interpretation * Data Annotation

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Data Annotation Engineer information

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$167K

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How much do data annotation engineer jobs pay per year?

As of Aug 23, 2026, the average yearly pay for data annotation engineer in Washington is $167,014.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,100.00 and $222,000.00 per year, depending on experience, location, and employer.

What is a data annotation engineer?

A Data Annotation Engineer is responsible for labeling and annotating data—such as text, images, audio, or video—to train machine learning models. They ensure that data is accurately categorized and structured to improve model performance. This role often involves using specialized annotation tools, following detailed guidelines, and working closely with data scientists and AI teams. Data Annotation Engineers play a crucial role in the development of AI applications by providing high-quality labeled datasets for supervised learning.

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

To thrive as a Data Annotation Engineer, you need a strong background in data analysis, attention to detail, and familiarity with annotation processes, often supported by a degree in computer science or a related field. Proficiency with annotation tools like Labelbox, CVAT, or VIA, and understanding of data formats used in machine learning, is commonly required. Excellent communication, collaboration, and organizational skills help you effectively manage projects and cooperate with cross-functional teams. These abilities are crucial for delivering high-quality labeled data, which directly impacts the performance of AI and machine learning models.

What are the main challenges faced by data annotation engineers in their daily work?

One of the main challenges Data Annotation Engineers face is ensuring consistent accuracy and quality in labeling large and often complex datasets. Attention to detail is critical, as even small errors can significantly affect machine learning model performance. Additionally, engineers must frequently adapt to evolving annotation guidelines and emerging data types, which requires ongoing learning and flexibility. Collaboration with data scientists and project managers is common to clarify requirements and resolve ambiguities, making strong communication skills essential for success.

What is the salary of data annotation engineer?

The salary of a data annotation engineer typically ranges from $40,000 to $80,000 annually, depending on experience, location, and the complexity of annotation tasks. Entry-level positions may start lower, while experienced professionals with specialized skills in tools like Labelbox or CVAT can earn higher salaries.

What are popular job titles related to Data Annotation Engineer jobs in Washington?

For Data Annotation Engineer jobs in Washington, the most frequently searched job titles are:

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The top searched job categories for Data Annotation Engineer jobs in Washington are:

What cities in Washington are hiring for Data Annotation Engineer jobs?

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Data Annotation Engineer jobs near you
Infographic showing various Data Annotation Engineer job openings in Washington as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 9% Part Time, 2% Temporary, and 7% Contract. Highlights an 81% Physical, 4% Hybrid, and 15% Remote job distribution, with an average salary of $167,014 per year, or $80.3 per hour.

Data & Annotation Engineer

Innodata Inc.

Washington, DC

$55 - $60/hr

Full-time

Re-posted 13 days ago

Innodata rating

7.5

Company rating: 7.5 out of 10

Based on 6 frontline employees who took The Breakroom Quiz

164th of 246 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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