Computer Vision Engineer – Soil Imaging & Laboratory AI
Core
Develop computer vision models and image analytics workflows for soil photography, XCT scans, and laboratory imaging to support geotechnical interpretation and digital twin initiatives.
Role type
Computer Vision Engineer (Scientific Imaging)
Builds
AI-enabled ground intelligence, Sample Quality Index, and image-derived inputs for laboratory testing.
Domain
Geotechnical engineering / Scientific imaging
Deliverable
production ML models
Required skills
Python, OpenCV, TensorFlow, image classification, segmentation, feature detection, object detection, image pre-processing, model validation, dataset annotation
Preferred skills
XCT/CT imaging analysis, voxel-based analysis, 3D volumetric image analysis, non-standard scientific datasets, cloud-based model deployment
Technologies
Python, OpenCV, TensorFlow
Responsibilities
Build image processing models for soil photographs and XCT scans; Analyze XCT images for soil structure and integrity; Develop image-based sample quality indicators; Establish image pre-processing and annotation workflows; Integrate image analytics with laboratory test results and digital twin analytics; Validate and document computer vision models against expert assessment.
Seniority
Mid-Senior, hands-on IC