ZipRecruiter

Log In

1

Home Based Medical Data Annotation Jobs in Washington

CaseGuard

Data Annotation Specialist

Arlington, VA

$40K - $50K/yr

We are seeking a detail-oriented Data Entry to support data preparation initiatives. This role is ... Medical, Dental, and Vision Insurance * 401K * Paid Vacation * Ten paid holidays per year

CaseGuard

Data Annotation Specialist

Arlington, VA · On-site

$40K - $50K/yr

We are seeking a detail-oriented Data Entry to support data preparation initiatives. This role is ... Medical, Dental, and Vision Insurance * 401K * Paid Vacation * Ten paid holidays per year

Innodata Inc.

AI Solutions Engineer

Washington, DC

$75 - $80/hr

Video understanding or FMV annotation experience * DataCard or ML data provenance framework familiarity The expected hourly salary range for this position is $75 to $80 p/hour, based on experience ...

Welo Data

Data Labeling Associate

Washington, DC

$34/hr

WHAT YOU'LL DO • Execute Data labelling and annotation tasks across speech and voice datasets ... • Medical, Dental, and Vision Insurance • Free Breakfast, Lunch, and Dinner (where applicable ...

next page

Showing results 1-20

All JobsHome Based Medical Data Annotation JobsHome Based Medical Data Annotation Jobs in Washington

Home Based Medical Data Annotation information

What are some common challenges faced by professionals working in home-based medical data annotation, and how can they be managed?

One common challenge in home-based medical data annotation is maintaining accuracy and consistency when labeling complex medical images or records, as errors can impact critical healthcare outcomes. Working remotely may also lead to feelings of isolation or difficulty staying updated with annotation guidelines. To manage these challenges, it's important to establish a quiet, dedicated workspace, participate in regular virtual team meetings, and utilize provided training resources. Staying engaged with peers through communication channels and seeking feedback from supervisors can also help ensure high-quality work and ongoing professional development.

What are the key skills and qualifications needed to thrive as a Home Based Medical Data Annotation Specialist, and why are they important?

To thrive as a Home Based Medical Data Annotation Specialist, you need a solid understanding of medical terminology, attention to detail, and experience with data labeling—often supported by a background in healthcare or life sciences. Familiarity with annotation platforms, EHR systems, and relevant data security protocols is typically required, and some employers may prefer certifications in medical coding or data management. Strong organizational skills, self-motivation, and effective written communication help individuals excel in remote, deadline-driven environments. These competencies ensure accurate, high-quality data labeling that is essential for developing reliable AI systems in healthcare.

What is the difference between Home Based Medical Data Annotation vs Home Based Medical Transcription?

AspectHome Based Medical Data AnnotationHome Based Medical Transcription
Required CredentialsBasic medical knowledge, attention to detailMedical terminology, transcription skills, sometimes certification
Work EnvironmentRemote, computer-basedRemote, computer-based
Industry UsageAI training, data labeling for healthcare AI modelsConverting audio to written reports for medical records
Common Search/ComparisonYesYes

Home Based Medical Data Annotation involves labeling medical images and data to train AI systems, requiring attention to detail and basic medical knowledge. In contrast, Home Based Medical Transcription focuses on converting audio recordings into written medical reports, often needing transcription skills and familiarity with medical terminology. Both roles are remote and industry-specific, but they serve different purposes within healthcare technology and documentation.

What is home based medical data annotation?

Home based medical data annotation involves labeling and categorizing medical data, such as images, audio, or text, from the comfort of your home. Annotators help train artificial intelligence (AI) systems by identifying and marking relevant information, such as highlighting tumors in X-rays or transcribing medical notes. This role is essential for improving the accuracy and efficiency of AI tools used in healthcare diagnostics, research, and patient care. Typically, it requires attention to detail, a basic understanding of medical terminology, and familiarity with annotation tools.
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 Home Based Medical Data Annotation jobs in Washington? For Home Based Medical Data Annotation jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Home Based Medical Data Annotation jobs in Washington look for? The top searched job categories for Home Based Medical Data Annotation jobs in Washington are:
What cities in Washington are hiring for Home Based Medical Data Annotation jobs? Cities in Washington with the most Home Based Medical Data Annotation job openings:
Home Based Medical Data Annotation jobs near you
Infographic showing various Home Based Medical Data Annotation job openings in Washington as of July 2026, with employment types broken down into 2% As Needed, 65% Full Time, 24% Part Time, 2% Temporary, 5% Contract, and 2% Nights. Highlights an 82% In-person, 4% Hybrid, and 14% Remote job distribution.
Data & Annotation Engineer

Data & Annotation Engineer

Innodata Inc.

Washington, DC

$55 - $60/hr

Other

Posted 16 days ago

Innodata rating

7.5

Company rating: 7.5 out of 10

Based on 6 frontline employees who took The Breakroom Quiz

162nd of 245 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

Hours and flexibility

Workplace

Get the full story on Breakroom

Apply