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Medical Image Annotation Jobs (NOW HIRING)

Voxelcloud

Machine Learning Engineer

Los Angeles, CA · On-site

... in medical scans, disease risk stratification, image synthesis, text report mining, and more! We ... Provide insights to data collection and annotation and collaborate with the data team for in-house ...

Voxelcloud

Machine Learning Engineer

Los Angeles, CA · On-site

... in medical scans, disease risk stratification, image synthesis, text report mining, and more! We ... Provide insights to data collection and annotation and collaborate with the data team for in-house ...

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Medical Image Annotation information

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$15

$37

$57

How much do medical image annotation jobs pay per hour?

As of Aug 23, 2026, the average hourly pay for medical image annotation in the United States is $37.30, according to ZipRecruiter salary data. Most workers in this role earn between $28.85 and $46.39 per hour, depending on experience, location, and employer.

What is medical image annotation?

Medical image annotation is the process of labeling or marking specific structures, regions, or abnormalities in medical images such as X-rays, CT scans, or MRIs. These annotations are crucial for training artificial intelligence (AI) models to assist in diagnostics, research, and treatment planning. Expert annotators, often with medical backgrounds, use specialized software to ensure accuracy and consistency. This work helps improve the performance of AI systems in identifying diseases and supporting healthcare professionals.

What are the key skills and qualifications needed to thrive as a medical image annotation specialist?

To excel as a Medical Image Annotation Specialist, you need a solid understanding of medical imaging modalities, anatomy, and basic clinical terminology, often supported by relevant education or experience in healthcare or life sciences. Familiarity with annotation software, image processing tools, and sometimes specialized platforms like DICOM viewers is typically required. Attention to detail, precision, and effective communication are crucial soft skills for ensuring accuracy and collaborating with clinical or research teams. These competencies are vital because high-quality, accurate annotations directly impact the development of AI models and the reliability of diagnostic tools in healthcare.

What are some common challenges faced by professionals in medical image annotation roles, and how can they be addressed?

Medical image annotation professionals often encounter challenges such as interpreting complex or ambiguous images, ensuring consistency across annotations, and keeping up with evolving medical guidelines. To address these challenges, many teams implement standardized protocols, regular training sessions, and peer review systems to maintain accuracy and reliability. Collaboration with radiologists and other medical experts is also common, allowing annotators to clarify uncertainties and improve the quality of annotations over time.

What is the difference between Medical Image Annotation vs Medical Data Labeling?

AspectMedical Image AnnotationMedical Data Labeling
Required CredentialsBasic understanding of medical imaging, attention to detailSimilar, often no formal certification needed
Work EnvironmentMedical imaging platforms, annotation toolsData management systems, labeling software
Industry UsageHealthcare, medical AI developmentHealthcare, medical AI, data analysis
Search & Comparison IntentYes, often compared for AI training rolesYes, related but broader in data types

Medical Image Annotation involves marking specific regions or features in medical images like X-rays or MRIs to train AI models. Medical Data Labeling encompasses annotating various medical data types, including images, text, and reports. While both roles support medical AI development, Image Annotation is specialized in visual data, whereas Data Labeling covers a wider range of medical information.

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Medical Image Annotation jobs near you
Infographic showing various Medical Image Annotation job openings in the United States as of August 2026, with employment types broken down into 10% As Needed, 70% Full Time, 5% Part Time, and 15% Contract. Highlights an 95% In-person, and 5% Remote job distribution, with an average salary of $77,580 per year, or $37.3 per hour.

Ophthalmologist (Medical Data Labeling Specialist)

Saviance

Boston, MA • On-site

Other

Re-posted 29 days ago

Job description

Ophthalmologist (Medical Data Labeling Specialist)
Location: India, Remote
Duration: Ongoing Part-Time
About BigRio
BigRio is a Boston-based, remote-first technology consulting firm specializing in advanced data and software solutions. We partner with forward-thinking organizations to deliver scalable, cost-effective, and innovative technology, with particular expertise in AI/ML, data engineering, and cloud-native applications. Our clients span healthcare, life sciences, government, and enterprise sectors, and we are known for our ability to tackle complex challenges with cutting-edge solutions.
About Job:
This role leverages the clinical expertise of an ophthalmologist to accurately annotate and label medical data, primarily images and structured clinical data related to eye health, for the development and refinement of artificial intelligence (AI) and machine learning (ML) models in ophthalmology.
Responsibilities
Key responsibilities include:
  • Data Annotation: Reviewing and annotating various ophthalmic data like fundus images, Optical Coherence Tomography (OCT) scans, and other visual data, identifying anatomical structures and disease markers.
  • Adherence to Protocols: Applying standardized grading protocols consistently for accurate and consistent labeling.
  • Quality Control & Feedback: Participating in calibration sessions and reviews to maintain annotation consistency.
  • Collaboration: Working with AI engineers and data scientists to ensure the clinical validity of guidelines.
  • AI Model Validation: Validating AI model outputs for clinical accuracy and safety.
  • Patient Education Material Development (potential): Possibly creating or reviewing materials for AI/ML algorithms to provide accurate patient education.
  • Privacy and Security: Ensuring compliance with patient privacy and data security policies, like HIPAA.
Qualifications
Essential qualifications typically include:
  • Ophthalmologist (MBBS) with at least 1-2 years of clinical experience.
  • Extensive Clinical Knowledge: In-depth understanding of various eye conditions.
  • Experience in Clinical Data Review: Familiarity with medical record documentation.
  • Attention to Detail: Commitment to accurate annotation.
  • Communication Skills: Excellent communication skills, both written and verbal, in English.
  • Teamwork: Ability to collaborate effectively with a multidisciplinary team.
Required skills often include:
  • Medical Image Annotation: Proficiency in using annotation tools to delineate structures and pathologies
  • Data Interpretation and Assessment: Skill in interpreting data related to medical products and AI model performance.
  • Problem Solving: Ability to identify challenges and recommend solutions.
  • Adaptability: Ability to adapt to varying image resolutions and file formats.

This role offers a unique opportunity to contribute to the development of AI tools that can improve eye health and patient care on a wider scale.
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About Saviance

Sourced by ZipRecruiter

Saviance is a modern consulting firm providing a variety of professional services to its clients in the US. We bring twenty three years of experience to the table. Our consultants are qualified experts and extremely talented. We understand the business behind the technology, and work with many of the top Fortune 100 companies and provide innovative, scalable, robust and secure solutions. At the forefront of the Staffing and IT Solutions industry, Saviance is certified by NMSDC as a Tier 1, Minority Business Enterprise (MBE) . We are a self- certified Small Business and self- certified Woman Owned Business committed to maximizing global workforce solutions on behalf of our clients, empowering businesses and talent through applied human intelligence. We are a Diversity Supplier with global reach specializing in a business services blend of talent, technology, and a relentless commitment to customer success. It’s our diversity that’s acts as a core component of our culture, our approach to business, and the opportunities we provide to our clients and our employees.

Industry

It services

Company size

201 - 500 Employees

Headquarters location

East Rutherford, NJ, US

Year founded

1999

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