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How much do from home 3d medical imaging post processing jobs pay per hour?

As of Aug 24, 2026, the average hourly pay for from home 3d medical imaging post processing in the United States is $24.67, according to ZipRecruiter salary data. Most workers in this role earn between $19.71 and $28.12 per hour, depending on experience, location, and employer.

What is a from home 3D medical imaging post processing specialist?

A From Home 3D Medical Imaging Post Processing job involves using specialized software to process, enhance, and analyze medical images—such as CT, MRI, or ultrasound scans—remotely from your own location. Professionals in this role transform raw image data into clear, 3D visualizations that help physicians diagnose and treat patients. This work requires a strong understanding of imaging technology, attention to detail, and the ability to communicate findings with healthcare teams, all performed in a secure remote environment.

What are the key skills and qualifications needed to thrive as a from home 3D medical imaging post processing specialist?

To excel in remote 3D medical imaging post processing, you need strong knowledge of anatomy, radiology principles, and advanced image reconstruction techniques, typically supported by a degree in radiologic technology or a related field. Proficiency with specialized software such as OsiriX, 3D Slicer, or GE AW Server, as well as familiarity with PACS and DICOM standards, is essential. Attention to detail, time management, and effective virtual communication are critical soft skills for delivering accurate results and collaborating with healthcare teams from a distance. These skills ensure precise diagnostics, timely workflow, and seamless integration with clinical teams, which are vital for patient care quality in a remote setting.

What are some common challenges faced by professionals working remotely in 3D medical imaging post processing?

Professionals in remote 3D medical imaging post processing often face challenges related to managing large data files, ensuring secure and fast internet connections, and maintaining effective communication with radiologists and clinical teams. It can also be more difficult to collaborate in real time on complex cases or receive immediate feedback when working from home. To overcome these challenges, many teams use secure cloud-based platforms and regularly scheduled video meetings to stay connected and maintain high-quality results.

What is the difference between From Home 3D Medical Imaging Post Processing vs From Home 3D Medical Imaging Technician?

AspectFrom Home 3D Medical Imaging Post ProcessingFrom Home 3D Medical Imaging Technician
CredentialsTypically requires certification in imaging software and post-processing skillsRequires certification or associate degree in radiologic technology or related field
Work EnvironmentRemote, computer-based post-processing tasksRemote or on-site, involving image acquisition and initial processing
Industry UsageUsed mainly in post-production, analysis, and interpretation of imaging dataInvolved in capturing images and initial processing in clinical settings

From Home 3D Medical Imaging Post Processing focuses on analyzing and refining imaging data remotely, while From Home 3D Medical Imaging Technician involves capturing images and initial processing, often in clinical environments. Both roles require specialized certifications but differ in daily tasks and work settings.

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From Home 3D Medical Imaging Post Processing jobs near you
Infographic showing various From Home 3D Medical Imaging Post Processing job openings in the United States as of August 2026, with employment types broken down into 80% Full Time, and 20% Part Time. Highlights an 87% In-person, and 13% Remote job distribution, with an average salary of $51,319 per year, or $24.7 per hour.

Research Scientist - Vision Foundation Models

Epsilon Health

San Francisco, CA • On-site

Full-time

Posted 24 days ago

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.)

Apply