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Medical Imaging Machine Learning Jobs in Chicago, IL

Senior Machine Learning Engineer (LLMs)

Chicago, IL ยท On-site

$126K - $166K/yr

Medical, dental, and vision coverage * 401(k) plan * High ownership and autonomy over your work ... Equipment and learning budget to help you do your best work and keep up with the frontier

Medical, dental, and vision coverage * 401(k) plan * High ownership and autonomy over your work ... Equipment and learning budget to help you do your best work and keep up with the frontier

Senior Machine Learning Engineer (LLMs)

Chicago, IL ยท On-site

$126K - $166K/yr

Medical, dental, and vision coverage * 401(k) plan * High ownership and autonomy over your work ... Equipment and learning budget to help you do your best work and keep up with the frontier

Develop and implement machine learning models and deliver accurate and quality analyses that ... This position offers a comprehensive benefits package that includes Medical, Dental, Vision ...

Develop and implement machine learning models and deliver accurate and quality analyses that ... This position offers a comprehensive benefits package that includes Medical, Dental, Vision ...

Showing results 41-60

Medical Imaging Machine Learning information

See Chicago, IL salary details

$23.1K

$93.9K

$198.1K

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

As of Aug 8, 2026, the average yearly pay for medical imaging machine learning in Chicago, IL is $93,947.00, according to ZipRecruiter salary data. Most workers in this role earn between $42,083.00 and $135,487.00 per year, depending on experience, location, and employer.

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.

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 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 most commonly searched types of Medical Imaging Machine Learning jobs in Chicago, IL? The most popular types of Medical Imaging Machine Learning jobs in Chicago, IL are:
What job categories do people searching Medical Imaging Machine Learning jobs in Chicago, IL look for? The top searched job categories for Medical Imaging Machine Learning jobs in Chicago, IL are:
Infographic showing various Medical Imaging Machine Learning job openings in Chicago, IL as of July 2026, with employment types broken down into 1% As Needed, 80% Full Time, 15% Part Time, and 4% Contract. Highlights an 90% Physical, 2% Hybrid, and 8% Remote job distribution, with an average salary of $93,947 per year, or $45.2 per hour.

Assistant Physicist

Argonne National Laboratory

Lemont, IL โ€ข On-site

Full-time

Re-posted 27 days ago


Job description

The X-ray Imaging Group (https://www.aps.anl.gov/Imaging) of the X-ray Science Division (XSD) operates the full-field x-ray imaging beamlines at the Advanced Photon Source (APS) (https://www.aps.anl.gov/) and pursues collaborative research across materials, energy, environmental, geo-, and life sciences using micro- and nano-tomography and high-speed imaging.
With the APS Upgrade driving a substantial increase in data rates and experimental complexity, the group is investing in AI/ML-driven software, automation, and autonomous experimentation, including a planned fully autonomous, AI-driven tomography beamline - to keep pace with user demand and unlock new science. This work is carried out in close coordination with the APS Computational science and AI (CAI) (https://cai.xray.aps.anl.gov/) group and other APS AI efforts and activities spanning data, computing, and machine learning across the facility. The appointee will benefit from access to world-leading experimental and computational resources at Argonne, including the upgraded APS and the exascale Aurora supercomputer.
We seek highly motivated candidates with strong expertise in AI/ML and in the development of AI tools for scientific operations to join the X-ray Imaging Group. The successful candidate will lead the design and deployment of AI-powered software that supports user operations, automates data acquisition and analysis, and enables closed-loop, autonomous experiments across the group's beamlines.
Position Responsibilities:
  • Design, develop, and deploy AI/ML tools for x-ray imaging operations including reconstruction, super-resolution, spatiotemporal fusion, denoising, segmentation, and feature extraction - and integrate them into the beamline software stack.

  • Build closed-loop experimental workflows in which AI agents use streaming data and real-time reconstruction and analysis to steer measurement decisions, and contribute to the development of a fully autonomous, AI-driven tomography beamline as a flagship project for the group.

  • Collaborate with the APS Computation and AI (CAI) group and engage with other APS AI efforts and activities to align Imaging Group tools with facility-wide AI/ML infrastructure, data services, and computing resources, and to contribute to shared frameworks for autonomous experimentation.

  • Develop automated pipelines for acquisition, quality control, and downstream analysis that translate beamline-scientist expertise and currently manual operational steps into robust, reusable software.

  • Build and maintain pipelines for robust metadata capture and the systematic generation of curated, standardized datasets to support continual AI/ML model training and validation.

  • Provide on-site support for user operations and data collection across the X-ray Imaging Group beamlines, working directly with beamline staff and users during experiments.

  • Contribute to the longer-term extension of AI-enabled automation and autonomy across Imaging Group modalities, including micro- and nano-tomography and high-speed imaging.

  • Prepare experiments and instruments for remote and AI-driven operation.

  • Present research results through publications, conferences, and scientific meetings.
  • May be required to perform other duties as assigned.

Position Requirements
  • Ph.D. in computer science, electrical engineering, computational physics, computational materials science, applied mathematics, or a closely related field.

  • Demonstrated expertise in AI/ML applied to imaging or scientific data, including hands-on experience developing and deploying deep-learning models (e.g., CNNs, vision transformers, diffusion models, or related architectures).

  • Strong scientific software development skills in Python and modern deep-learning frameworks (e.g., PyTorch, TensorFlow), including experience with distributed training on high-performance computing resources.

  • Experience with high-performance computing (HPC) and/or cloud environments.

  • Experience with version control (e.g., Git) and collaborative software development practices.

  • Experience working with experimental imaging data, ideally at a synchrotron, electron microscopy, medical imaging, or comparable facility.

  • Ability to work effectively both independently and in a collaborative, team-based research environment.

  • Ability to model Argonne's core values of impact, safety, respect, integrity, and teamwork.

  • Interpersonal skills, oral and written communication skills, and ability to interact with people at all levels both within and outside the laboratory.

Preferred Knowledge, Skills, and Experience
  • Experience developing AI/ML methods specifically for x-ray imaging, tomography, or high-speed imaging applications.

  • Experience designing or contributing to automated, remote, or closed-loop ("self-driving") experimental workflows, including real-time data reduction, on-the-fly reconstruction, and AI-based experimental steering.

  • Experience collaborating with facility-level computing, data, or AI groups to deploy software into production scientific environments.

  • Experience handling high-rate, large-volume imaging datasets and developing high-throughput reconstruction or analysis pipelines.

  • Experience contributing to open-source scientific software projects.

  • Familiarity with metadata standards, data management, and curation practices that support reproducible science and ML training datasets.

  • Familiarity with beamline data acquisition systems, detectors, or controls software, sufficient to integrate AI tools into operational workflows.

Job Family
Research Development (RD)
Job Profile
Physics 2
Worker Type
Regular
Time Type
Full time
The expected hiring range for this position is $94,486.00 - $147,398.94.
Please note that the pay range information is a general guideline only. The pay offered to a selected candidate will be determined based on factors such as, but not limited to, the scope and responsibilities of the position, the qualifications of the selected candidate, business considerations, internal equity, and external market pay for comparable jobs. Additionally, comprehensive benefits are part of the total rewards package.
Click here to view Argonne employee benefits!
As an equal employment opportunity employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a safe and welcoming workplace that fosters collaborative scientific discovery and innovation. Argonne encourages everyone to apply for employment. Argonne is committed to nondiscrimination and considers all qualified applicants for employment without regard to any characteristic protected by law.
Argonne employees, and certain guest researchers and contractors, are subject to particular restrictions related to participation in Foreign Government Sponsored or Affiliated Activities, as defined and detailed in United States Department of Energy Order 486.1A. You will be asked to disclose any such participation in the application phase for review by Argonne's Legal Department.
All Argonne offers of employment are contingent upon a background check that includes an assessment of criminal conviction history conducted on an individualized and case-by-case basis. Please be advised that Argonne positions require upon hire (or may require in the future) for the individual be to obtain a government access authorization that involves additional background check requirements. Failure to obtain or maintain such government access authorization could result in the withdrawal of a job offer or future termination of employment.