Medical Imaging Data & AI Engineer (Associate)

Philips; Massachusetts; On-site; USD 100,000 - 158,000; Full time

Job summary

Philips in Bedford, MA is hiring an Associate Data & AI Engineer focused on medical imaging. You will curate and annotate X-ray coronary angiography datasets and collaborate with clinical, engineering, and data science teams to advance imaging algorithms.

The role involves designing and testing image-processing algorithms in Python using PyTorch and TensorFlow, enabling deployment, documenting methods, and contributing to QA and regulatory workflows.

Qualifications

• Bachelor's or master's in engineering, computer science, physics, mathematics, or biomedical imaging.
• Experience developing algorithms with Python; familiar with PyTorch and TensorFlow.
• Experience building GUI-based data annotation tools with Tk or Napari.
• Strong knowledge of image- and signal-processing concepts and numerical methods.
• Experience validating algorithm performance on imaging datasets.
• Strong problem-solving, written and verbal communication skills.

Responsibilities

• Source, curate, and annotate X-ray coronary angiography datasets to support model development and validation.
• Collaborate with clinical, engineering, and data science teams; define imaging-related algorithmic solutions and present progress.
• Design, implement, and test image-processing algorithms in Python using TensorFlow and PyTorch; support deployment and debugging.
• Document code, algorithm designs, and validation methods; contribute to regulatory and QA workflows for algorithms.
• Explore GPU/CUDA optimization techniques; share knowledge across teams.

Skills

Python

PyTorch

TensorFlow

GUI tools (Tk, Napari)

Image processing

CUDA optimization

Education

Bachelor's or Master's in Engineering/CS/Physics/Math/Biomedical Imaging

Tools

Napari

Tkinter

CUDA

Job description

Philips in Bedford, MA is hiring an Associate Data & AI Engineer focused on medical imaging. You will curate and annotate X-ray coronary angiography datasets and collaborate with clinical, engineering, and data science teams to advance imaging algorithms.

The role involves designing and testing image-processing algorithms in Python using PyTorch and TensorFlow, enabling deployment, documenting methods, and contributing to QA and regulatory workflows.