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Ai Annotation Jobs in Springfield, VA (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 ... You'll work with the AI Solutions Engineer to ensure the data going into our models is accurate ...

Innodata Inc.

AI Solutions Engineer

Washington, DC · On-site

$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 ...

YO AI Labs

AI Finance Expert - Remote

Washington, DC · Remote

$100 - $200/hr

AI Finance Domain Expert Job Type: Contractor (Part-Time) Location: Remote Job Overview We are ... Data Annotation * Problem-Solving * Independent Research * Attention to Detail Preferred ...

YO AI Labs

AI Consulting Expert - Remote

Washington, DC · Remote

$100 - $200/hr

Job Title: AI Consulting Domain Remote Job Type: Contractor (Part-Time) Location: Remote Job ... Data Annotation * Fact Checking * Independent Research * Problem-Solving * Attention to Detail ...

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Ai Annotation information

See Springfield, VA salary details

$104.7K

$138.7K

$182.4K

How much do ai annotation jobs pay per year?

As of Sep 4, 2026, the average yearly pay for ai annotation in Springfield, VA is $138,664.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,700.00 and $169,200.00 per year, depending on experience, location, and employer.

What is an AI annotation?

An AI Annotation job involves labeling, tagging, or annotating data, such as images, text, or audio, to train machine learning models. Annotators help improve AI accuracy by providing high-quality, structured data that algorithms use to learn patterns. Tasks may include identifying objects in images, transcribing speech, or classifying text-based content. This job is essential for developing AI applications like self-driving cars, chatbots, and image recognition systems.

What does an AI annotation specialist do?

As an AI Annotation specialist, your typical day will involve accurately labeling, categorizing, or tagging large volumes of images, text, audio, or video data to train AI models according to project guidelines. You may work independently or as part of a team, using specialized annotation platforms and regularly reviewing your work to ensure quality and consistency. Collaboration with data scientists or project managers may be required to clarify ambiguous cases or update labeling criteria. You can expect periodic feedback and performance reviews to help refine your skills and ensure the data meets the project’s standards, making attention to detail and adaptability essential for success.

What are the key skills and qualifications needed to thrive in the AI annotation position?

To thrive as an AI Annotation professional, you need keen attention to detail, strong analytical skills, and a basic understanding of machine learning concepts, often supported by a high school diploma or relevant technical training. Familiarity with data labeling tools, annotation platforms such as Labelbox or Supervisely, and basic spreadsheet or database management is commonly required. Strong communication, time management, and the ability to maintain focus during repetitive tasks are standout soft skills. These abilities are crucial for producing high-quality, consistent data that supports the effective development and accuracy of AI models.

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Ai Annotation jobs near you
Infographic showing various Ai Annotation job openings in Springfield, VA as of August 2026, with employment types broken down into 49% Full Time, 21% Part Time, and 30% Contract. Highlights an 45% In-person, and 55% Remote job distribution, with an average salary of $138,664 per year, or $66.7 per hour.

Data & Annotation Engineer

Innodata Inc.

Washington, DC • On-site

$55 - $60/hr

Full-time

Re-posted 26 days ago

Key responsibilities

  • Administer the annotation toolchain, manage annotation workflows, and produce documentation for governance.

  • Configure and operate the CVAT annotation pipeline during corpus production.

  • Support quality control and associate provenance records with annotated and synthetic outputs.

Innodata rating

7.5

Company rating: 7.5 out of 10

Based on 6 frontline employees who took The Breakroom Quiz

165th of 247 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

What Innodata employees say

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