ZipRecruiter

Log In

1

Radiology Data Annotation Jobs (NOW HIRING)

micro1

Radiologist

$327K - $409K/yr

... advanced annotation project. In this role, you'll apply your expertise to help train next ... data. * Review visual feedback, identify deviations from requirements, and make targeted ...

A2z Radiology

$140K - $180K/yr

... data is involved. You can disagree with a radiologist about software, and you defer to them ... annotation tooling from either side; AWS and Terraform; segmentation or computer vision; inter ...

STG International

Radiology Technician

Sherman, TX · On-site

Performs quality control of the images, assessing for proper exposure, positioning and annotation ... Performs routine archiving status checks and deletes data according to established guidelines.

STG International

Radiology Technician

Sherman, TX

Performs quality control of the images, assessing for proper exposure, positioning and annotation ... data and images. Monitors the patient's physical condition, physiologic changes during the ...

Honorhealth

Interventional Radiology Tech

Osborn, SC · On-site

Performs data entry operations using appropriate hospital software package. Staff member may be ... marking and annotation as required by IR procedure protocols. * Utilizes RIS, PACS and other ...

Honorhealth

Interventional Radiology Tech

Phoenix, AZ · On-site

Performs data entry operations using appropriate hospital software package. Staff member may be ... marking and annotation as required by IR procedure protocols. * Utilizes RIS, PACS and other ...

HonorHealth

Interventional Radiology Tech

Phoenix, AZ · On-site

Performs data entry operations using appropriate hospital software package. Staff member may be ... marking and annotation as required by IR procedure protocols. * Utilizes RIS, PACS and other ...

HonorHealth

Interventional Radiology Tech

Phoenix, AZ · On-site

Performs data entry operations using appropriate hospital software package. Staff member may be ... marking and annotation as required by IR procedure protocols. * Utilizes RIS, PACS and other ...

SME Careers

Radiologist

$327K - $409K/yr

Radiology AI Content Developer MD/DO (or equivalent) with completed Radiology residency (Diagnostic ... Prior experience with AI data training/annotation, report QA, peer review, utilization management ...

Worky

Clinical Imaging Platform Engineer

Boston, MA · On-site

$140K - $180K/yr

Our annotation pipeline measures itself: race-free case claiming, per-annotator phase progression ... You default to fail-closed with patient data. * Enough taste to disagree with a radiologist about ...

HonorHealth

Radiologic Tech - Lead

Scottsdale, AZ · On-site

Performs data entry operations using appropriate hospital software package. Staff member may be ... and annotation as required by Radiology procedure protocols. Utilizes RIS, PACS and other ...

next page

Showing results 1-20

All JobsHealthcare JobsHospital JobsMedical Transcription JobsRadiology Data Annotation Jobs

Radiology Data Annotation information

See salary details

$44K

$74.2K

$107K

How much do radiology data annotation jobs pay per year?

As of Sep 11, 2026, the average yearly pay for radiology data annotation in the United States is $74,164.00, according to ZipRecruiter salary data. Most workers in this role earn between $54,500.00 and $94,500.00 per year, depending on experience, location, and employer.

What is radiology data annotation?

Radiology data annotation is the process of labeling and tagging medical images such as X-rays, CT scans, and MRIs with relevant information to assist in training artificial intelligence (AI) models. Annotators, often trained professionals, highlight areas of interest or mark abnormalities to ensure that the AI systems can learn to identify diseases or patterns from the images. This work is crucial in developing accurate diagnostic tools and improving the efficiency of radiology workflows.

What are some common challenges faced in radiology data annotation, and how can they be addressed?

Radiology data annotation often involves interpreting complex medical images, which can be challenging due to subtle findings or ambiguous cases. Annotators must ensure high accuracy and consistency, often collaborating closely with radiologists to validate findings and resolve uncertainties. It's important to stay updated on evolving annotation protocols and utilize quality control tools to minimize errors. Continuous learning and regular feedback from clinical experts can help address these challenges and improve annotation quality.

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

To excel as a Radiology Data Annotation Specialist, you need a solid understanding of medical imaging concepts, attention to detail, and familiarity with radiological terminology, often supported by a background in healthcare or life sciences. Experience with annotation platforms, DICOM viewers, and image labeling tools, as well as knowledge of HIPAA compliance, is typically required. Strong analytical skills, communication, and the ability to work independently are valuable soft skills in this role. These competencies ensure accurate and efficient data labeling, which is critical for developing reliable AI models and supporting clinical research.

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

AspectRadiology Data AnnotationMedical Image Labeling
CredentialsTypically requires knowledge of radiology and basic medical terminologySimilar, often requires understanding of medical imaging
Work EnvironmentHealthcare settings, remote or on-site data labsHealthcare or research institutions, remote or on-site
Industry UsageUsed in AI model training for radiology diagnosticsUsed in developing medical imaging AI tools

Radiology Data Annotation and Medical Image Labeling are closely related roles focused on preparing medical images for AI training. While both require understanding of medical images, radiology data annotation often involves detailed annotations like segmentations, whereas medical image labeling may focus on classifying images. Both roles are vital in advancing medical AI applications.

What other helpful pages are available for Radiology Data Annotation?

Other pages related to Radiology Data Annotation:

Infographic showing various Radiology Data Annotation job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 84% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution, with an average salary of $74,164 per year, or $35.7 per hour.

Physician Annotator - Nuclear Medicine Clinical AI (Part-Time/Contract)

New York, NY • On-site, Remote

NUC S.A.I.
See more jobs at NUC S.A.I.external

Contractor

Re-posted 21 days ago

Key responsibilities

  • Perform reviews of nuclear medicine imaging exams and provide clinical insight and annotations to support AI model training and refinement.

  • Validate AI outputs for clinical accuracy, safety, and relevance across defined use cases.

  • Provide clinical feedback on product features and workflows to inform development and improvement.

Job description

About Us
Nucs AI is a pioneering MedTech startup focused on transforming prostate cancer care through advanced AI-driven software solutions. Our mission is to deliver personalized treatment options that enhance patient outcomes and streamline clinical workflows. We collaborate with leading medical institutions and pharmaceutical companies globally to achieve groundbreaking results in patient care.
Role Overview
Nucs AI is entering a significant phase of growth as we expand our capabilities across nuclear molecular imaging and broaden the clinical applications of our AI-driven products. As we scale, we are strengthening our clinical annotation and validation efforts to ensure our models remain accurate, relevant, and tightly aligned with real-world oncology care. To support this expansion, we are seeking an experienced Physician Annotator to play a critical role in the development and continuous improvement of our clinical AI solutions.
This role combines hands-on nuclear medicine imaging study review, structured clinical annotation, and thoughtful product feedback to ensure AI models are clinically accurate, reliable, and aligned with real-world care delivery. The Physician Annotator will serve as a key bridge between clinical practice, data science, and product teams - bringing practical expertise to annotation standards, model validation, workflow evaluation, and performance refinement.
As part of a fast-moving, clinically grounded AI team, you will directly contribute to how advanced imaging technologies are translated into trusted tools that support physician decision-making and improve cancer care delivery at scale.
Key Responsibilities
Clinical Expertise
  • As a subject matter expert contribute to the development and refinement of annotation protocols and clinical guidelines for different use cases.
  • Identify edge cases, ambiguities, and potential sources of bias in clinical data and model behavior
  • Participate in applied clinical AI research, including hypothesis development and evaluation of model performance.
  • Assist in generating research insights that may inform internal studies, publications, or regulatory documentation

Clinical Annotation & Validation
  • Perform reviews of nuclear medicine imaging exams and provide clinical insight and annotations to support AI model training and refinement. Clinical review tasks include review of studies with and without AI assistance for identification and delineation of areas of interest on a variety of nuclear medicine images (e.g., FDG, PSMA-PET/CT, SPECT) with precision and accuracy.
  • Validate AI outputs for clinical accuracy, safety, and relevance across defined use cases.
  • Review model errors and edge cases; provide structured clinical insights to improve performance.
  • Advise on clinically meaningful metrics, thresholds, and evaluation criteria.

Strategic product feedback
  • Provide concise, actionable clinical feedback on product features and workflows.
  • Advise product teams on feature prioritization based on clinical impact, risk, and feasibility.
  • Support retrospective and prospective analyses to assess clinical validity and real-world utility of AI models.
  • Evaluate usability and workflow integration from a clinician's perspective.

Cross-Functional Collaboration
  • Collaborate asynchronously with clinical, product, and data science teams.
  • Serve as a part-time clinical advisor supporting rapid iteration and informed decision-making.

Why Join Nucs AI
  • Work at the frontier of clinical AI: Help advance next-generation oncology tools in nuclear molecular imaging.
  • Have real clinical influence: Your work and feedback directly shape model performance, product behavior, and clinical reliability.
  • High scientific rigor: Contribute to clinically grounded development with a strong focus on safety, accuracy, and real-world validity.
  • Collaborate with a high-caliber team: Work closely with clinicians, engineers, and data scientists who move fast and value clarity.
  • Flexible by design: Part-time, contract, and fully remote with flexible hours (location restrictions may apply).
  • Mission that matters: Help improve how cancer care is delivered - at scale, and with real patient impact.

Required Qualifications
  • ABR/ABNM Board certified physician with minimum 3 or more years of experience in Nuclear Medicine (or Diagnostic Radiology with subspecialty certification in Nuclear Medicine).
  • Active, unrestricted medical license in the US.
  • Possesses demonstrated expertise in interpreting PET imaging for radioligand tracers such as FDG, PSMA, and SSTR, and in radioligand therapies.
  • Exceptional attention to detail and a commitment to producing high-quality work.

Preferred Experience
  • Prior experience with healthcare AI, digital health, or clinical informatics.
  • Experience with data annotation, clinical validation, or quality review.
  • Familiarity with ML concepts, model evaluation, or human-in-the-loop systems.
  • Experience advising on product strategy or clinical product development.

Apply