Machine Learning Engineer – MRI Imaging Segmentation

Job Overview
We are seeking an experienced Machine Learning Engineer to join our team on a freelance basis for a medical imaging project. The role involves developing AI-driven solutions for segmenting MRI scans, helping to enhance visualization and analysis for healthcare professionals. Working remotely, you will design and implement deep learning models that process DICOM medical images and integrate these models into an existing infrastructure.
Key Responsibilities

Develop and train AI models for MRI segmentation using deep learning frameworks (e.g., PyTorch or TensorFlow).
Handle medical imaging data in DICOM format, including preprocessing and transformation using libraries like pydicom, OpenCV, and ITK.
Utilize specialized frameworks like MONAI or nnU-Net to leverage established best practices in healthcare AI.
Integrate segmentation models into a web application or service using Flask or FastAPI, enabling clinicians to interact with model outputs.
Manage data storage and retrieval by interfacing with AWS S3 for image storage and PostgreSQL for metadata/results.
Ensure robust deployment by containerizing the application (Docker) and possibly orchestrating workloads on AWS or Kubernetes for scalability.
Collaborate with the team (including radiologists) to refine model accuracy and validate results in a clinical context.

Requirements

Proficiency in Python and experience with deep learning libraries (e.g., PyTorch, TensorFlow).
Hands-on knowledge of medical imaging (DICOM files) and relevant libraries (pydicom, ITK).
Familiarity with MONAI or similar medical AI frameworks, demonstrating knowledge of segmentation techniques in healthcare imaging.
Web integration skills: Experience creating APIs or services with Flask/FastAPI to host and serve AI models.
Cloud & Databases: Experience with AWS (especially S3) and a relational database like PostgreSQL.
Deployment know-how: Ability to containerize applications using Docker; understanding of AWS or other cloud environments for hosting.
Medical imaging background: Prior exposure to MRI, CT, or similar image data; an understanding of noise, resolution, and domain-specific challenges.

Preferred Qualifications

Previous medical AI projects: Demonstrated experience working on segmentation solutions in the medical imaging field.
Collaboration with clinicians: History of integrating feedback from radiologists or medical professionals into AI workflows.
Knowledge of VTK.js/Three.js or other 3D visualization libraries is a plus (though not essential).
Advanced education or research: A graduate degree in a relevant field (Computer Science, Biomedical Engineering) or publications in medical imaging AI.
Strong portfolio: Examples or case studies of similar segmentation projects that can be shared.

How to Apply
If you are interested in this opportunity, please send your CV (résumé) and any portfolio of relevant segmentation projects to our team via email. In your message, provide a brief overview of your experience with medical imaging and suggest a few time slots when you are available to discuss the project in more detail. We will review applications on a rolling basis and schedule a meeting with qualified candidates to explore fit and expectations.
We look forward to reviewing your application and potentially working together on this cutting-edge medical imaging segmentation initiative!
Job Types: Contract, Temporary
Pay: $50.00 - $65.00 per hour
Work Location: Remote