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Medical Image Deep Learning Jobs (NOW HIRING)

Voxelcloud

Machine Learning Engineer

Los Angeles, CA

... in medical scans, disease risk stratification, image synthesis, text report mining, and more! We ... Develop deep learning models for prototyping and production purposes according to product feature ...

Voxelcloud

Machine Learning Engineer

Los Angeles, CA · On-site

... in medical scans, disease risk stratification, image synthesis, text report mining, and more! We ... Develop deep learning models for prototyping and production purposes according to product feature ...

Nucs AI

Machine Learning Scientist

Berlin, MA · On-site +1

... image analysis (CNNs, transformers, U-Nets, etc.) * Strong programming skills in Python and deep learning frameworks (PyTorch preferred) * Experience working with medical imaging data (PET/CT, MRI ...

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Medical Image Deep Learning information

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$28K

$45K

$58.5K

How much do medical image deep learning jobs pay per year?

As of Aug 3, 2026, the average yearly pay for medical image deep learning in the United States is $45,043.00, according to ZipRecruiter salary data. Most workers in this role earn between $38,500.00 and $48,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Medical Image Deep Learning position, and why are they important?

To thrive in Medical Image Deep Learning, a strong background in computer science, machine learning, and medical imaging, typically supported by an advanced degree (MS/PhD) in a relevant field, is essential. Familiarity with deep learning frameworks such as TensorFlow or PyTorch, experience with medical image formats (DICOM, NIfTI), and knowledge of regulatory guidelines are often required. Strong analytical thinking, problem-solving skills, and the ability to work collaboratively with multidisciplinary healthcare teams are valued soft skills. These qualifications are crucial for developing accurate, reliable AI models that can positively impact patient care and diagnostic workflows.

What does a typical day look like for someone working in Medical Image Deep Learning?

A typical day in Medical Image Deep Learning often involves designing, implementing, and testing deep learning algorithms on various medical imaging datasets, such as MRI or CT scans. Professionals regularly collaborate with radiologists, data scientists, and software engineers to refine models and ensure clinical relevance. Routine responsibilities include data preprocessing, model tuning, result interpretation, and thorough documentation of findings. Additionally, team members may participate in research meetings, code reviews, and contribute to publishing scientific results or developing new features for healthcare applications.

What is a Medical Image Deep Learning job?

A Medical Image Deep Learning job involves developing AI models that analyze medical images, such as X-rays, MRIs, and CT scans, to assist in disease detection, diagnosis, and treatment planning. Professionals in this field apply deep learning techniques like convolutional neural networks (CNNs) to extract meaningful patterns from medical images. They work closely with healthcare professionals to ensure models are accurate, reliable, and interpretable for clinical use.

More about Medical Image Deep Learning jobs
What are the most commonly searched types of Medical Image Deep Learning jobs? The most popular types of Medical Image Deep Learning jobs are:
What job categories do people searching Medical Image Deep Learning jobs look for? The top searched job categories for Medical Image Deep Learning jobs are:
Medical Image Deep Learning jobs near you
Infographic showing various Medical Image Deep Learning job openings in the United States as of July 2026, with employment types broken down into 75% Full Time, 17% Part Time, and 8% Contract. Highlights an 100% In-person job distribution, with an average salary of $45,043 per year, or $21.7 per hour.

Deep Learning Expert/Developer (On-site)

Ripple Effect

Bethesda, MD • On-site

$90K - $103K/yr

Full-time

Posted 7 days ago

Job description

General Information
  • Job Code: SHR-BI-03
  • Location: NIH Campus onsite, with ad-hoc telework
  • Employee Type: Exempt, Full-Time Regular
  • Clearance: Must be able to work in the U.S. without employer sponsorship
  • Salary Range: $90,267-$103,808 (how we pay and promote) 
Position Overview

Are you passionate about turning complex data into meaningful insights? As a Deep Learning Developer on the Ripple Effect team, you will play a pivotal role in shaping our success in this important role with the NIH! Your work will directly impact the Lister Hill Center's work. This position involves applying deep learning techniques to biomedical images and clinical data for clinical decision-making and prediction. The role focuses on the development of tools for retinal disease detection, severity classification, disease progression prediction, and more. The ideal candidate will have a strong background in deep learning, particularly for medical image analysis, and experience with high-performance computing environments.

While not an exhaustive list, the key duties for the position include:

    • Develop deep learning models to support clinical decision-making for retinal diseases using retinal images, genomic data, and clinical records.
    • Develop algorithms for disease detection, severity classification, and longitudinal progression prediction, focusing on retinal diseases as well as other patient data.
    • Build and optimize deep learning tools for deployment on Android/iOS/Web-based platforms.
    • Other related duties as assigned.

Requirements

Minimum Qualifications
  • Master's degree
  • 5 or more years of experience in image analysis, machine learning, and deep learning
Basic Requirements
    • Proven experience writing manuscripts or papers for journals and conferences.
    • Extensive experience with medical image processing, data analysis, and classification techniques.
    • Expertise in developing custom deep learning workflows, including visualizing activations.
    • Strong understanding of machine learning techniques, including Support Vector Machines (SVM), Multilayer Perceptron (MLP), and Convolutional Neural Networks (CNNs).
    • Proficiency in Decision Tree algorithms such as Random Forest, XGBoost, and LightGBM.
    • Experience in statistical analysis of experimental results.
    • Familiarity with Linux and Windows environments.
    • Hands-on experience with high-performance GPU clusters and multi-GPU setups for deep learning tasks.
    • Expertise in programming with Python, Keras, and PyTorch.
    • Experience in developing Android, iOS, or web applications.
    • Must reside within a commutable distance from the NIH main campus in Bethesda, MD, and be willing to report on site on a daily basis for this role.

Skills That Set You Apart

  • PhD in computer science, computer engineering, or relevant field
  • Familiarity with Linux and Windows environments.
  • Intermediate experience with (levels 03+) Microsoft Office productivity software and collaboration tools such as Microsoft Teams and SharePoint. 
  • Intermediate experience with workplace AI tools, including their limitations and risks, and how they can be applied to support project management tasks.   

About Ripple Effect

Ripple Effect is a woman-owned, 200-person company of communicators, scientists, researchers, and analysts. Established in 2003, and named as one of the “Best and Brightest Companies to Work For” in 2024 and 2025 by the NABR, Ripple Effect has earned acclaim for delivering unparalleled consulting services and top-tier talent across federal, private, and non-profit sectors.

Benefits

At Ripple Effect, we reward our employees for their contributions to our mission. Our comprehensive total rewards package includes competitive pay, exceptional benefits, and a range of programs that support your work/life balance and personalized preferences.

Learn more about our benefits and culture here.