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Medical Image Annotation Jobs in Rutherford, NJ (NOW HIRING)

HSS

Research Intern

New York, NY · On-site

$20 - $23.75/hr

What You'll Learn • Fundamentals of musculoskeletal MRI anatomy • How AI segmentation models are trained and validated in a clinical setting • Practical experience with medical image annotation ...

Tt

AI & Computer Vision Intern

New York, NY

Labeling platforms: experience with image or point cloud annotation tools (e.g., Supervisely, CVAT ... Medical, Dental, Vision, Life, AD&D, Disability and other voluntary benefits * Flexible Spending ...

All JobsMedical Image Annotation JobsMedical Image Annotation Jobs in Rutherford, NJ

Medical Image Annotation information

See Rutherford, NJ salary details

$15

$38

$59

How much do medical image annotation jobs pay per hour?

As of Jun 26, 2026, the average hourly pay for medical image annotation in Rutherford, NJ is $38.02, according to ZipRecruiter salary data. Most workers in this role earn between $29.42 and $47.31 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 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.

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

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 job categories do people searching Medical Image Annotation jobs in Rutherford, NJ look for? The top searched job categories for Medical Image Annotation jobs in Rutherford, NJ are:
What cities near Rutherford, NJ are hiring for Medical Image Annotation jobs? Cities near Rutherford, NJ with the most Medical Image Annotation job openings:
Medical Image Annotation jobs near you
Infographic showing various Medical Image Annotation job openings in Rutherford, NJ as of June 2026, with employment types broken down into 32% Internship, 8% As Needed, 24% Full Time, 27% Part Time, and 9% Contract. Highlights an 89% In-person, and 11% Remote job distribution, with an average salary of $79,088 per year, or $38 per hour.
Research Intern

Research Intern

HSS

New York, NY • On-site

$20 - $23.75/hr

Part-time

Posted 6 days ago

Job description

How you move is why we're here. ®
Now more than ever.
Get back to what you need and love to do.
The possibilities are endless...
Now more than ever, our guiding principles are helping us in our search for exceptional talent - candidates who align with our unique workplace culture and who want to maximize the abundant opportunities for growth and success.
If this describes you then let's talk!
HSS is consistently among the top-ranked hospitals for orthopedics and rheumatology by U.S. News & World Report. As a recipient of the Magnet Award for Nursing Excellence, HSS was the first hospital in New York City to receive the distinguished designation. Whether you are early in your career or an expert in your field, you will find HSS an innovative, supportive and inclusive environment.
Working with colleagues who love what they do and are deeply committed to our Mission, you too can be part of our transformation across the enterprise.
Emp Status
Per Diem Part time
Work Shift
Day (United States of America)
Compensation Range
The base pay scale for this position is $20.00 - $23.75. In addition, this position will be eligible for additional benefits consistent with the role. The salary of the finalist selected for this role will be determined based on various factors, including but not limited to: scope of role, level of experience, education, accomplishments, internal equity, budget, and subject to Fair Market Value evaluation. The hiring range listed is a good faith determination of potential compensation at the time of this job advertisement and may be modified in the future.
What you will be doing
What You'll Do
• Review knee MRI scans using a web-based annotation tool, no installation required
• Manually correct AI-generated segmentations of knee anatomy, including bones, cartilage, and ligament attachment surfaces
• Work through a queue of assigned cases
• Flag cases with unusual anatomy or image quality issues for expert review
No prior MRI experience is required. Training is provided on knee anatomy, image contrast, and use of the annotation tool, typically completed within one day.
What You'll Learn
• Fundamentals of musculoskeletal MRI anatomy
• How AI segmentation models are trained and validated in a clinical setting
• Practical experience with medical image annotation and quality control
• Exposure to an active clinical AI development program at a leading orthopedic institution
Who We're Looking For
• College students or recent high school graduates pursuing biomedical engineering, computer science, biology, pre-medicine, or a related field
• Available for approximately 10 hours per week over 8 weeks during summer 2026
• Detail-oriented and comfortable with repetitive, precision-focused work
• Interest in medical imaging, AI, or orthopedic surgery is a plus, but not required
Non-Discrimination Policy
Hospital for Special Surgery is committed to providing high quality care and skilled, compassionate, reliable service to our community in a safe and healing environment. Consistent with this commitment, Hospital for Special Surgery provides care, admits, and treats patients and provides all services without regard to age, race, color, creed, ethnicity, religion, national origin, culture, language, physical or mental disability, socioeconomic status, veteran or military status, marital status, sex, sexual orientation, gender identity or expression, or any other basis prohibited by federal, state, or local law or by accreditation standards.

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