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Medical Imaging Machine Learning Jobs (NOW HIRING)

Duke University

Postdoctoral Associate

Durham, NC · On-site

As a Postdoctoral Associate in Diagnostic Imaging & Machine Learning , you will join an innovative research team dedicated to advancing next-generation medical imaging technologies. Your expertise in ...

Duke University

Postdoctoral Associate

Durham, NC · On-site

As a Postdoctoral Associate in Diagnostic Imaging & Machine Learning , you will join an innovative research team dedicated to advancing next-generation medical imaging technologies. Your expertise in ...

Natera

Machine Learning Scientist, Multimodal AI

OR · On-site +1

Core experience developing machine learning models for biomedical applications, specifically in medical imaging, computational pathology, genomics, transcriptomics, multi-omics, or molecular ...

Natera

Machine Learning Scientist, Multimodal AI

$124K - $171K/yr

Core experience developing machine learning models for biomedical applications, specifically in medical imaging, computational pathology, genomics, transcriptomics, multi-omics, or molecular ...

Ports North

NY · On-site

$120 - $180/hr

This individual will leverage large-scale medical imaging datasets to build machine learning models that identify abnormalities, prioritize critical studies, automate report generation, and enhance ...

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Medical Imaging Machine Learning information

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$22.5K

$91.5K

$193K

How much do medical imaging machine learning jobs pay per year?

As of Aug 21, 2026, the average yearly pay for medical imaging machine learning in the United States is $91,529.00, according to ZipRecruiter salary data. Most workers in this role earn between $41,000.00 and $132,000.00 per year, depending on experience, location, and employer.

What is a medical imaging machine learning?

A Medical Imaging Machine Learning job involves developing and applying artificial intelligence (AI) techniques to analyze medical images, such as X-rays, MRIs, and CT scans. Professionals in this field use machine learning models to assist in disease detection, diagnosis, and treatment planning. They work with large medical datasets, optimize deep learning models, and collaborate with radiologists and healthcare professionals to improve diagnostic accuracy and efficiency. The role requires expertise in machine learning, computer vision, and medical imaging technologies.

What are the key skills and qualifications needed to thrive in medical imaging machine learning?

To excel in Medical Imaging Machine Learning, a solid background in computer science, machine learning, and image processing, often supported by an advanced degree (MS or PhD) in a related field, is essential. Experience with programming languages like Python, deep learning frameworks such as TensorFlow or PyTorch, and familiarity with medical imaging standards (like DICOM) are commonly required. Strong analytical thinking, problem-solving abilities, and the ability to communicate complex technical concepts to multidisciplinary teams are highly valued. These competencies enable professionals to develop and implement effective AI solutions that enhance diagnostic accuracy and workflow efficiency in healthcare settings.

What types of teams do medical imaging machine learning professionals typically work with, and how is collaboration structured?

Medical Imaging Machine Learning specialists often collaborate closely with radiologists, data scientists, software engineers, and clinical researchers to develop and refine AI-driven diagnostic tools. The work environment is usually multidisciplinary, involving regular meetings, code reviews, and joint problem-solving sessions to ensure alignment between technical solutions and clinical needs. Team members may also work with regulatory experts to ensure compliance with healthcare standards. This collaborative approach ensures that models are both technically robust and clinically relevant, ultimately supporting better patient outcomes.

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Medical Imaging Machine Learning jobs near you
Infographic showing various Medical Imaging Machine Learning job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 15% Part Time, and 7% Contract. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution, with an average salary of $91,529 per year, or $44 per hour.

Imaging Machine Learning Engineer

Socket.dev

Mountain View, CA • On-site

$132 - $189/hr

Other

Posted 8 days ago

Job description

Minimum qualifications:
  • Bachelor’s degree in Electrical Engineering, Computer Science, Imaging Science, Physics, or a related field, or equivalent practical experience.
  • 2 years of experience in Image Quality, Computer Vision, or a related technical field.
  • 2 years of experience in Python and C++ for algorithm development and implementation.
Preferred qualifications:
  • Master’s degree, or PhD in a related field.
  • 3 years of professional experience in a related field.
  • Industry experience in SoC/ISP constraints, 3A tuning, or the application of Deep Learning to real-time imaging pipelines.
  • A proven track record of delivering high-quality, commercial, market-facing consumer cameras.
  • A strong track record of self-driven learning and the capability to rapidly master new technologies and domains.
  • Excellent written and verbal communication skills, with a demonstrated ability to translate technical concepts into clear, actionable insights for cross-functional partners.
About the job:

The Platforms and Devices team encompasses Google's various computing software platforms across environments (desktop, mobile, applications), as well as our first party devices and services that combine the best of Google AI, software, and hardware. Teams across this area research, design, and develop new technologies to make our user's interaction with computing faster and more seamless, building innovative experiences for our users around the world. Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $132000 - $189000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities:
  • Optimize image quality across the hardware and software stack, ensuring hardware capabilities are leveraged through software tuning.
  • Fine-tune 3A algorithms to ensure performance across lighting and environmental conditions.
  • Build software tools, utilizing machine learning (ML) automation to streamline image quality (IQ) tuning, testing, benchmarking, and calibration workflows.
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