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Data Annotation Engineer Jobs in Washington (NOW HIRING)

Innodata Inc.

AI Solutions Engineer

Washington, DC

$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 ...

New

Beyond SOF

DATA ENGINEER

Reston, VA · On-site

$119K - $143K/yr

Java -JDK 1.6+, Model View Controller (MVC) architecture, Annotation, Servelet 2.5/Java Server ... SSL programming and configuration, CAPCO (rules and automated parsing or validation). Access ...

Gormat

Data Scientist 3

Annapolis Junction, MD · On-site

Ability to use analytic modeling, statistical analysis, programming, and/or another appropriate ... annotation of language data with parts of speech information, and improved existing models by ...

Gormat

Data Scientist 3

Annapolis Junction, MD · On-site

$132K - $147K/yr

Ability to use analytic modeling, statistical analysis, programming, and/or another appropriate ... annotation of language data with parts of speech information, and improved existing models by ...

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All JobsData Annotation Engineer JobsData Annotation Engineer Jobs in Washington

Data Annotation Engineer information

See Washington salary details

$58.3K

$167K

$223.1K

How much do data annotation engineer jobs pay per year?

As of Jul 12, 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 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 are the key skills and qualifications needed to thrive in the Data Annotation Engineer position, and why are they important?

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.

Does data annotation really pay?

Data annotation engineers can earn competitive wages, often paid hourly or per task, with pay rates varying based on experience, complexity of annotations, and the platform or employer. Entry-level roles may start at minimum wage, while experienced annotators or those with specialized skills can earn higher salaries or freelance rates. Overall, data annotation can provide a reliable income, especially for remote or flexible work arrangements.

What is the highest salary for data annotator?

The highest salary for a data annotation engineer can reach up to $80,000 to $100,000 annually, depending on experience, location, and the complexity of annotation tasks. Senior roles or those with specialized skills in tools like Labelbox or CVAT may earn higher compensation. Salaries vary widely across companies and regions but generally reflect the technical skills required for high-quality data labeling.

What is a data annotation engineer?

A data annotation engineer is a professional responsible for labeling and annotating data, such as images, text, or videos, to prepare it for machine learning models. They often use specialized tools and follow guidelines to ensure data quality, supporting the development of AI systems.

How hard is it to get hired by data annotation?

Getting hired as a data annotation engineer typically requires basic computer skills, attention to detail, and familiarity with annotation tools. Many positions are entry-level and may not require advanced degrees, but strong accuracy and consistency are important for success in the role.

What is a Data Annotation Engineer job?

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 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:
What job categories do people searching Data Annotation Engineer jobs in Washington look for? The top searched job categories for Data Annotation Engineer jobs in Washington are:
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Data Annotation Engineer jobs near you
Infographic showing various Data Annotation Engineer job openings in Washington as of July 2026, with employment types broken down into 83% Full Time, and 17% Contract. Highlights an 90% In-person, and 10% Remote job distribution, with an average salary of $167,014 per year, or $80.3 per hour.
Data & Annotation Engineer

Data & Annotation Engineer

Innodata Inc.

Washington, DC

$55 - $60/hr

Other

Posted 2 days ago

New

Innodata rating

7.3

Company rating: 7.3 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

151st of 209 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 for the program's largest payment milestone ($131,250). Candidates must be genuinely comfortable operating CVAT at production quality against a mission dataset under a milestone deadline

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