Medical Visualization Engineer 3D Rendering

Key Responsibilities

• Develop interactive medical visualization applications for 2D images, multiplanar reconstruction, 3D surfaces, and volumetric datasets derived from CT, MR, ultrasound, or fluoroscopy workflows.
• Implement volume rendering, surface rendering, transfer functions, lighting, clipping, cropping, transparency, camera controls, and anatomical exploration features.
• Convert medical image volumes, segmentation masks, landmarks, centerlines, meshes, and quantitative results into accurate and intuitive 3D visual representations.
• Develop visualization features for segmentation overlays, measurements, annotations, registration results, treatment or intervention planning, and image-guided navigation.
• Implement geometry-processing workflows including isosurface extraction, mesh generation, smoothing, decimation, repair, normal computation, and model export.
• Optimize rendering pipelines for responsiveness, memory efficiency, GPU utilization, and real-time interaction with large medical datasets.
• Work with DICOM datasets and support image loading, orientation handling, voxel spacing, coordinate transformations, metadata interpretation, and de-identification-aware workflows.
• Collaborate with AI and medical imaging teams to visualize model outputs, uncertainty, anatomical structures, and quantitative biomarkers for validation and demonstration.
• Conduct visual and functional testing to verify anatomical correctness, coordinate consistency, rendering quality, usability, and performance across representative datasets.
• Document visualization architecture, rendering methods, design assumptions, performance findings, and user-interface behavior.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Computer Graphics, Biomedical Engineering, Electrical Engineering, Medical Imaging, Game Technology, or a related field.
• Less than 3 years of professional, research, internship, or project experience in computer graphics, scientific visualization, medical imaging, game-engine development, or 3D application development.
• Strong understanding of 3D graphics concepts including coordinate systems, transformations, cameras, lighting, textures, meshes, shaders, depth, transparency, and rendering pipelines.
• Hands-on programming experience in C++ and/or Python, with exposure to graphics or visualization frameworks.
• Experience with one or more tools or libraries such as VTK, OpenGL, WebGL, Three.js, Unity, Unreal Engine, DirectX, Vulkan, or similar technologies.
• Experience working with 3D geometry, point clouds, surface meshes, volumetric data, or image stacks.
• Familiarity with image-processing and medical-imaging tools such as OpenCV, SimpleITK, ITK, pydicom, NiBabel, MONAI, or 3D Slicer.
• Understanding of DICOM image orientation, voxel spacing, patient coordinate systems, resampling, and the relationship between image space and world space.
• Ability to profile and troubleshoot rendering performance, memory use, visual artifacts, and cross-platform behavior.
• Good communication skills and ability to work collaboratively with imaging scientists, AI engineers, clinicians, UX designers, and software developers.

Preferred Skills

• Experience with direct volume rendering, ray casting, transfer-function design, GPU shaders, CUDA, compute shaders, or GPU-accelerated image processing.
• Exposure to medical visualization workflows such as MPR, MIP, MinIP, curved planar reformation, cinematic rendering, segmentation review, surgical planning, or navigation.
• Familiarity with mesh-processing libraries such as Open3D, PCL, CGAL, trimesh, MeshLab, or similar frameworks.
• Experience creating interactive desktop, web, AR, VR, or mixed-reality applications for scientific or medical use cases.
• Basic understanding of human factors, visual perception, color mapping, accessibility, and clinical usability considerations.

Good to have

• Exposure to front-end development frameworks such as React, Angular, Qt, Flutter, or similar technologies for building visualization interfaces and proof-of-concept demos.
• Experience with DICOMweb, PACS integration concepts, image streaming, cloud-based rendering, or remote visualization.
• Awareness of regulatory, privacy, cybersecurity, and software-quality considerations for medical visualization applications, including traceability and reproducible validation.