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Manager 3D Medical Imaging Post Processing Jobs in California

Koobz

3D Printing Process Engineer

Ventura, CA

$80K - $120K/yr

Create G-code post-processing scripts to enhance workflow and efficiency. * Conduct research and ... Comprehensive insurance (medical, dental, and vision). * A generous Employee Stock Option Plan.

Community Health System

Medical Imaging Manager

Fresno, CA · On-site

$65.25 - $83.03/hr

As the Manager, Medical Imaging, you will lead a team that is a regional leader in advanced, patient centered care. You will partner closely with imaging leadership to drive: * Operational excellence

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Manager 3D Medical Imaging Post Processing information

What is the difference between Manager 3D Medical Imaging Post Processing vs Radiology Technologist?

AspectManager 3D Medical Imaging Post ProcessingRadiology Technologist
CredentialsAdvanced certifications in imaging software, management experienceCertification in radiologic technology (ARRT or equivalent)
Work EnvironmentImaging departments, post-processing labs, healthcare facilitiesHospitals, clinics, diagnostic imaging centers
Employer & IndustryMedical imaging companies, hospitals, healthcare providersHospitals, outpatient clinics, diagnostic centers
Job FocusOverseeing 3D image processing, managing teams, quality controlPerforming imaging procedures, patient positioning, image acquisition

The main difference is that the Manager 3D Medical Imaging Post Processing focuses on overseeing the post-processing of 3D medical images and managing teams, while the Radiology Technologist performs the actual imaging procedures and patient care. Both roles require specialized certifications and work within healthcare settings, but their responsibilities differ significantly.

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Manager 3D Medical Imaging Post Processing jobs near you

Research Scientist - Vision Foundation Models

Epsilon Health

San Francisco, CA • On-site

Full-time

Posted 2 days ago

New

Job description

About Us
We're tackling one of healthcare's most critical challenges in medical imaging and diagnostics. Our company operates at the intersection of cutting-edge AI and clinical practice, building technology that directly impacts patient outcomes. We've assembled one of the industry's most comprehensive and diverse medical imaging datasets and have a proven product-market fit with a substantial customer pipeline already in place.
Role Overview
We're seeking a Research Scientist with deep expertise in vision foundation models to join our ML Research team. You'll be at the forefront of developing and deploying state-of-the-art vision models for medical imaging applications. This role focuses on pretraining and scaling vision encoders for radiology diagnosis across X-ray, CT, and MRI, with a growing emphasis on 3D volumetric modeling. You'll work with one of the largest and most diverse medical imaging datasets in the industry, pushing the boundaries of what's possible in AI-assisted diagnosis while maintaining the rigor required for clinical deployment.
Key Responsibilities
  • Design, train, and scale vision foundation models for radiology applications across X-ray, CT, and MRI modalities, implementing self-supervised, contrastive, masked image modeling, and joint-embedding predictive (JEPA) frameworks.
  • Extend 2D pretraining recipes to volumetric CT and MR data, addressing long sequence lengths, anisotropic spacing, and multi-sequence studies.
  • Evaluate model performance rigorously across academic benchmarks, internal offline datasets, and live production data.
  • Contribute hands-on to all stages of model development including dataset curation, architecture design, distributed training, and production deployment.
  • Stay current with cutting-edge research in computer vision and medical imaging AI.
  • Drive research and technical excellence through conference publications and technical blog posts, establishing best practices for training robust medical imaging models at scale.
Qualifications
  • 6+ years of academia/industry experience in computer vision/machine learning
  • Deep expertise in training vision encoder models at scale (e.g. ViT, ConvNeXt). Strong foundation in self-supervised pretraining, including contrastive, masked image modeling, self-distillation, and JEPA-style objectives.
  • Experience training on volumetric or spatiotemporal data (video, 3D medical imaging)
  • Track record of implementing complex models from research papers and adapting them to new domains
  • Proficiency in PyTorch or JAX, with experience training models on multi-GPU/distributed systems
  • Hands-on experience with medical imaging applications, particularly radiology (X-ray, CT, MRI)
  • Strong software engineering skills and ability to write production-quality code
Preferred Qualifications
  • Publications at top-tier conferences (CVPR, ICCV/ECCV, NeurIPS, ICLR, MICCAI)
  • Experience with 3D medical image processing and retrieval tasks
  • Familiarity with CT and MR acquisition (windowing, multi-sequence protocols, voxel spacing)
  • Experience with long-context training techniques (sequence parallelism, efficient attention)
  • Knowledge of vision-language models and multimodal learning
  • Experience with model interpretability and explainability methods
  • Understanding of clinical evaluation metrics, clinical workflows, and healthcare data (DICOM, HL7, etc.)

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