1 month ago
Munich, GermanyStaff+
Responsibilities
- Design and optimize machine learning and deep learning models for 3D point cloud filtering, denoising, registration, and surface reconstruction.
- Own 3D data pipelines from preprocessing and augmentation through model adaptation and evaluation against ground-truth geometry.
- Integrate 3D machine learning solutions into existing workflows and products in collaboration with AI researchers, software engineers, and product designers.
- Adapt state-of-the-art 3D deep learning methods, including point-based, sparse voxel or convolutional, graph-based, transformer-based, and diffusion-based approaches, for production use.
- Build scalable and reproducible training pipelines for large 3D datasets.
- Analyze geometric and perceptual quality metrics to improve model performance and raise the team’s expertise in 3D machine learning.
Requirements
- MS or PhD in computer vision, machine learning, computer science, or a related field, or equivalent practical experience.
- 5–7+ years of hands-on experience applying machine learning and deep learning to point cloud processing, filtering, registration, or surface reconstruction.
- Strong theoretical grounding in machine learning, deep learning, geometry, linear algebra, and optimization.
- Familiarity with point cloud-specific architectures, including PointNet++, sparse convolutional networks, graph neural networks, and transformer- or diffusion-based 3D models.
- Strong Python skills and hands-on experience with PyTorch, TensorFlow, and Scikit-learn.
- Fluent English communication skills for cross-functional collaboration.
- Preferred qualifications include computer graphics and GPU programming experience; experience with NeRF, Gaussian splatting, or signed distance functions; familiarity with ML experimentation and orchestration tools; relevant publications or open-source projects; experience with C++ and 3D libraries; and Linux experience.
Benefits
- 30 days of paid time off per year.
- Subsidized access to EGYM Wellpass fitness and wellness facilities.
- Deutschlandticket subsidy for public transportation.
- Flexible working hours and a hybrid work setup.
- Full visa and relocation support for international candidates.
- Bike leasing through JobRad.
- Competitive compensation package.
- Employee referral bonus.
- Financial support for local language classes.
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