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Medical Imaging Segmentation Jobs (NOW HIRING)

Stryker

Senior Computer Vision Engineer

Menlo Park, CA · On-site

$116K - $193K/yr

... 3D medical imaging segmentation, deriving biomarkers from medical imaging such as CT scans, X-Ray, MRI, etc. * Collaborate with internal or external teams in acquiring, storing, organizing ...

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Medical Imaging Segmentation information

What are the key skills and qualifications needed to thrive as a Medical Imaging Segmentation Specialist, and why are they important?

To excel in Medical Imaging Segmentation, you need a solid background in biomedical engineering, computer science, or related fields, with expertise in image analysis and anatomy. Familiarity with medical imaging software (such as 3D Slicer or ITK-SNAP), programming languages (like Python), and machine learning frameworks is typically required. Attention to detail, strong problem-solving skills, and effective communication are critical soft skills for accurately interpreting images and collaborating with clinical teams. These skills ensure precise, reliable segmentation that supports diagnostics, research, and treatment planning in medical settings.

What are some common challenges faced in medical imaging segmentation roles, and how can they be addressed?

Professionals working in medical imaging segmentation often encounter challenges such as dealing with low-quality or noisy imaging data, anatomical variability among patients, and the need for precise delineation of structures. These challenges can be addressed by developing strong skills in image preprocessing, leveraging advanced segmentation algorithms (such as deep learning methods), and collaborating closely with radiologists or clinicians to validate results. Regular communication with multidisciplinary teams and staying updated with the latest research also help in overcoming these obstacles and improving segmentation accuracy.

What is medical imaging segmentation?

Medical imaging segmentation is the process of partitioning medical images, such as CT, MRI, or ultrasound scans, into meaningful regions or structures. This technique helps identify and isolate specific tissues, organs, or abnormalities, making it easier for clinicians to analyze and diagnose medical conditions. Segmentation can be done manually, semi-automatically, or automatically using advanced algorithms, including artificial intelligence. It is a critical step in many medical applications, such as treatment planning, disease monitoring, and surgical navigation.
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Medical Imaging Segmentation jobs near you
Infographic showing various Medical Imaging Segmentation job openings in the United States as of July 2026, with employment types broken down into 4% As Needed, 69% Full Time, 15% Part Time, and 12% Contract. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution.
Senior Data Scientist, Medical Imaging

Senior Data Scientist, Medical Imaging

Formation Bio

Boston, NY • On-site

$177K - $232K/yr

Other

Posted 6 days ago

Job description

About the Position

As a Senior Data Scientist - Medical Imaging at Formation Bio, you will lead our efforts to integrate advanced imaging analytics and AI into our drug development pipeline. In this role, you'll pioneer the application of computer vision and deep learning to medical imaging data (MRI, X-ray, CT, PET) to accelerate clinical trials and improve patient outcomes. You'll develop state-of-the-art models for automated image analysis, disease progression monitoring, and treatment response assessment. Working closely with clinical teams, radiologists, and drug development experts, you'll translate complex imaging data into actionable insights that drive key decisions across our portfolio. This position offers a unique opportunity to revolutionize how medical imaging is leveraged in pharmaceutical development while directly impacting patient care.

Responsibilities

  • Lead the development of advanced deep learning models for medical image analysis, focusing on MRI and X-ray modalities for clinical trial applications
  • Design and implement automated image processing pipelines for disease detection, segmentation, and quantification across multiple therapeutic areas
  • Create innovative approaches for longitudinal image analysis to track disease progression and treatment efficacy in clinical trials, incl. AI-based biomarkers and surrogate endpoints
  • Collaborate with clinical operations to integrate imaging AI solutions into trial protocols and workflows
  • Partner with regulatory teams to ensure imaging biomarkers and AI models meet FDA standards for clinical trial endpoints
  • Build scalable infrastructure for processing and analyzing large-scale medical imaging datasets from multi-site clinical trials
  • Present imaging insights and model performance to executive leadership and external partners

About You

Required Qualifications 

  • PhD in Computer Science, Biomedical Engineering, Medical Physics, or related field with focus on medical imaging
  • 5+ years of post-PhD industry experience developing production-grade AI models for medical imaging applications
  • Deep expertise in computer vision and deep learning architectures (CNNs, U-Net, Vision Transformers) for medical image analysis
  • Proven track record with MRI and X-ray image analysis, including hands-on experience with DICOM standards and medical imaging software
  • Strong programming skills in Python with expertise in PyTorch/TensorFlow and medical imaging libraries
  • Demonstrated ability to collaborate with radiologists and clinical teams to translate medical insights into technical solutions
  • Strong communication skills with proven ability to present complex imaging analytics to diverse stakeholders

Preferred Qualifications 

  • Experience with regulatory submissions involving imaging endpoints or AI-based image analysis tools
  • Experience with multi-modal imaging fusion and analysis (combining MRI, CT, PET data)
  • Knowledge of clinical trial design and experience with imaging core lab operations
  • Experience with federated learning or privacy-preserving techniques for medical imaging
  • Understanding of radiomics and quantitative imaging biomarker development
  • Experience with 3D image reconstruction and volumetric analysis

Total Compensation Range: $177,500 - $232,000

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