Posted Oct 12, 2026 53 views
We are seeking a talented 3D Computer Vision Engineer to tackle a challenging engineering problem: accurately mapping structural anomalies and defects identified in 2D images onto 3D meshes created by single-image AI reconstruction pipelines. In this role, you will design, implement, and refine the processes that connect localized 2D defect photos with AI-generated 3D geometries. Your work will involve camera calibration, single-image depth estimation, and 3D spatial alignment to develop an automated, web-based asset inspection platform.
Key Responsibilities
- Algorithm Development: Create and implement reliable 2D-to-3D mapping pipelines that project localized 2D defect imagery onto AI-generated building meshes with high accuracy.
- Camera Pose & Alignment: Develop algorithms leveraging feature matching techniques such as SIFT, ORB, and LoFTR, alongside perspective estimation methods like PnP and homography, to dynamically align multi-angle or close-up inspection photos with a single-image base model.
- Texture Baking & UV Mapping: Build automated workflows to manipulate texture UV spaces, ensuring that 2D defect data is cleanly and permanently baked onto model textures without distortion or bleed-through.
- Pipeline Integration: Work directly with modern single-view 3D reconstruction AI models (e.g., TripoSR, LRM, SV3D, or custom architectures) to extract camera intrinsics, depth maps, and mesh coordinates.
- Performance Optimization: Enhance spatial tracking and 3D ray-casting processes to enable real-time or near-real-time processing of imagery captured by drones or handheld devices.
Required Qualifications
- Bachelor’s, Master’s, or PhD degree in Computer Science, Robotics, Data Science, or a related field with a strong emphasis on Computer Vision.
- 2 to 4+ years of practical industry experience developing spatial computing, photogrammetry, or 3D digital twin software applications.
- Proven expertise working with mesh geometries such as OBJ and GLTF/GLB formats, including their texture structures.
- Strong problem-solving skills, particularly when handling imperfect or low-resolution mesh data generated by AI models.
- Proficiency in 3D and vision libraries including OpenCV, Open3D, PyTorch3D, or Trimesh.
- Familiarity with 3D web rendering technologies such as Three.js, WebGL, or Babylon.js for mesh visualization and ray-casting in web environments.
- Deep understanding of linear algebra, camera intrinsic and extrinsic matrices, projective geometry, coordinate system transformations, and UV mapping.
- Advanced programming skills in Python and experience with standard machine learning and data science toolkits.
- Experience with deep learning frameworks like PyTorch or TensorFlow, especially in neural depth estimation, Neural Radiance Fields (NeRFs), or 3D Gaussian Splatting architectures.
Preferred Qualifications and Benefits
- Competitive salary, allowances, and benefits package.
- Flexible and hybrid work arrangements to support work-life balance.
- The unique opportunity to contribute to pioneering generative AI technologies that have tangible, real-world physical impact.
This role offers a chance to work at the forefront of 3D computer vision and AI-driven inspection technologies, combining cutting-edge research with practical application in asset management and structural analysis.
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DataStallion
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