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From Home Medical Data Annotation Jobs in Washington

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 ... Receive, validate, ingest, and ontology-map the ODIN mission-aligned corpus from AFS delivery

TAD PGS, Inc

Video Annotation Support

Laurel, MD · On-site

$30 - $35/hr

Annotation of video data collected by small unmanned aircraft and surface vessels. The annotation ... medical coverage plan, and DailyPay (in some locations). For a full description of benefits ...

New

TAD PGS, Inc.

Video Annotation Support

Laurel, MD

$30 - $35/hr

Annotation of video data collected by small unmanned aircraft and surface vessels. The annotation ... medical coverage plan, and DailyPay (in some locations). For a full description of benefits ...

New

TAD PGS, Inc

Video Annotation Support

Laurel, MD

$30 - $35/hr

Annotation of video data collected by small unmanned aircraft and surface vessels. The annotation ... medical coverage plan, and DailyPay (in some locations). For a full description of benefits ...

New

Innodata Inc.

Senior Data Annotator

Washington, DC · On-site

Own annotation quality for a delivery team. A Senior Annotator personally handles the hardest ... Coach individuals using specific examples from their own reviewed work, and confirm the correction ...

New

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From Home Medical Data Annotation information

What is a from home medical data annotation job?

A work from home medical data annotation job involves labeling and categorizing medical data, such as images, text, or audio, to help train artificial intelligence systems used in healthcare. This typically means identifying and tagging important information within medical records, radiology images, or clinical notes so that machine learning models can better understand and process the data. These roles are mostly remote, allowing individuals to work from their own homes while contributing to the development of advanced healthcare technologies. Attention to detail and a basic understanding of medical terminology are often required.

What are the key skills and qualifications needed to thrive as a from home medical data annotation specialist, and why are they important?

To succeed as a From Home Medical Data Annotation Specialist, you need a background in medical terminology, attention to detail, and familiarity with clinical data formats, often supported by relevant coursework or experience in healthcare or data management. Proficiency with data annotation platforms, medical coding systems (such as ICD-10 or CPT), and secure remote work tools is frequently required. Strong soft skills include self-motivation, time management, and clear written communication to ensure accuracy and meet deadlines independently. These skills are crucial for producing high-quality, reliable annotated data that supports medical research, AI model development, and healthcare decision-making.

What are the main challenges of working as a medical data annotator from home, and how can they be addressed?

One of the main challenges of working as a medical data annotator from home is maintaining consistent focus and accuracy when handling large volumes of sensitive patient data. Distractions at home, limited direct supervision, and potential technology issues can also impact productivity. To address these, it's important to establish a dedicated workspace, follow strict data security protocols, regularly communicate with your team, and utilize project management tools to track progress. Many employers also provide training and ongoing support to help remote annotators stay compliant with privacy regulations and quality standards.

What is the difference between From Home Medical Data Annotation vs Medical Data Labeler?

AspectFrom Home Medical Data AnnotationMedical Data Labeler
CredentialsBasic computer skills, attention to detailSimilar credentials, often no formal certification required
Work EnvironmentRemote, home-basedRemote, home-based
Industry UsageHealthcare, AI trainingHealthcare, AI, machine learning
Job FocusAnnotating medical images and data for AI modelsLabeling medical data for machine learning algorithms

Both roles involve remote work and require attention to detail, focusing on medical data annotation and labeling for AI applications. The main difference lies in terminology; 'From Home Medical Data Annotation' emphasizes the annotation process, while 'Medical Data Labeler' highlights the labeling aspect. Both positions are essential in healthcare AI development and share similar credentials and work environments.

What are the most commonly searched types of Medical Data Annotation jobs in Washington?

The most popular types of Medical Data Annotation jobs in Washington are:

What are popular job titles related to From Home Medical Data Annotation jobs in Washington?

For From Home Medical Data Annotation jobs in Washington, the most frequently searched job titles are:

What job categories do people searching From Home Medical Data Annotation jobs in Washington look for?

The top searched job categories for From Home Medical Data Annotation jobs in Washington are:

What cities in Washington are hiring for From Home Medical Data Annotation jobs?

Cities in Washington with the most From Home Medical Data Annotation job openings:

From Home Medical Data Annotation jobs near you

Data & Annotation Engineer

Washington, DC • On-site

Innodata Inc.
IT Services • 501 - 1,000 employees
Learn more about Innodata Inc.external

$55 - $60/hr

Full-time

Re-posted 3 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

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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