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Permanent Ai Annotation Writing Jobs in Washington

Innodata Inc.

Data & Annotation Engineer

Washington, DC

$55 - $60/hr

... write-back capabilities. About the Role: As the Data/Annotation Engineer, you'll be hands-on with ... 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

Validate AI feature integration end-to-end across storefront, annotation platform, and DataCard write-back during Phase C Must-Have Qualifications: * Bachelor's degree in Computer Science, Machine ...

micro1 AI

AI Trainer - Microbiology Expert

Alexandria, VA · Remote

$70 - $90/hr

Provide written and verbal expertise on microbiological phenomena and their relevance to real-world ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

micro1 AI

AI Trainer - Microbiology Expert

Washington, DC · Remote

$70 - $90/hr

Provide written and verbal expertise on microbiological phenomena and their relevance to real-world ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

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Permanent Ai Annotation Writing information

What is permanent AI annotation writing?

Permanent AI Annotation Writing jobs involve the ongoing task of labeling and annotating data—such as text, images, audio, or video—so that artificial intelligence systems can learn and improve. Annotators use specialized tools to identify objects, actions, or features in datasets, providing crucial information that helps train AI models. These positions are typically long-term or full-time, offering stability and the opportunity to develop expertise in AI data preparation. Workers in this field often collaborate with data scientists and engineers to ensure high-quality, accurate annotations. The demand for skilled annotators is growing as AI applications expand into more industries.

What are some typical challenges faced by professionals in permanent AI annotation writing roles, and how can they be addressed?

In permanent AI annotation writing roles, professionals often encounter challenges such as maintaining high accuracy and consistency across large volumes of data, adapting to evolving project guidelines, and managing repetitive tasks. To address these challenges, it's important to develop a systematic approach to annotation, regularly review updated instructions, and collaborate closely with quality assurance teams. Utilizing productivity tools and participating in team discussions can also help streamline workflows and reduce errors, ensuring that the annotated data meets the required standards for AI model training.

What are the key skills and qualifications needed to thrive as a permanent AI annotation writer?

To thrive as a Permanent AI Annotation Writer, you need excellent attention to detail, strong language proficiency, and a basic understanding of data labeling principles, often supported by relevant coursework or experience in linguistics or data science. Familiarity with annotation tools like Labelbox or Prodigy, and experience following annotation guidelines or taxonomies, are commonly required. Strong communication, critical thinking, and the ability to work independently are valuable soft skills in this role. These skills ensure high-quality, consistent data labeling, which directly impacts the performance and reliability of AI models.
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Permanent Ai Annotation Writing jobs near you

Data & Annotation Engineer

Innodata Inc.

Washington, DC

$55 - $60/hr

Other

Posted 27 days ago

Innodata rating

7.5

Company rating: 7.5 out of 10

Based on 6 frontline employees who took The Breakroom Quiz

161st of 242 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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