Lead Machine Learning Engineer - Geometric Spatial AI (F/M/D) at NavVis
At a glance
- Company
- NavVis
- Location
- Munich, Germany
- Work arrangement
- Hybrid
- Employment type
- Full-time
- Experience
- 5–10 years
- Working hours
- 40 hours
- Visa sponsorship
- Offered, according to the listing
- Posted
- Added to The Stack
✨ The Stack take on this NavVis job
- 🏢 NavVis has 20 jobs here, 18 with visa sponsorship see all
- 📊 4 Machine Learning Engineer jobs in Germany in the last 60 days see them
- 🛂 Visa: EU Blue Card. Minimum salary: €50,700 a year guide
- 💡 No salary shown. Ask NavVis if it is above the minimum.
Updated 2026-11-01, from our data and official sources.
About the role
Responsibilities:
- Design and optimize ML/DL models for 3D point cloud tasks: filtering, denoising, registration, and surface reconstruction.
- Own end-to-end 3D data pipelines: preprocessing, augmentation, training, evaluation, and model adaptation to ground-truth geometry.
- Adapt state-of-the-art 3D architectures (point-based, sparse conv, GNNs, implicit/neural representations) for production use.
- Integrate ML solutions into product workflows and collaborate with researchers, engineers, and product teams.
- Build scalable, reproducible training and deployment pipelines and improve models using geometric and perceptual metrics.
Requirements:
- MS/PhD in computer vision, ML, CS, or equivalent practical experience.
- 5–7+ years applying ML/DL to point cloud or 3D data, with strong theoretical grounding in geometry and deep learning.
- Proficiency in Python and ML frameworks (PyTorch/TensorFlow); C++/CUDA experience is a strong plus.
- Familiarity with point-cloud architectures (e.g., PointNet++), sparse convolutional methods, GNNs, and tools like Open3D.
- Experience moving research into production, working with large 3D datasets, and building scalable ML pipelines.
Responsibilities
Design and optimize machine learning models for 3D point cloud data, including filtering, registration, and surface reconstruction. Manage end-to-end 3D data pipelines and integrate these solutions into production workflows.
Requirements
Requires an MS or PhD in a relevant field and 5-7+ years of hands-on experience in machine learning and 3D data processing. Candidates must possess strong Python skills and a solid theoretical foundation in geometry and deep learning architectures.
Key skills
- Machine Learning — in 276 other listings on The Stack
- Deep Learning — in 47 other listings on The Stack
- 3D Point Cloud Processing — not in any other listing on The Stack
- Computer Vision — in 29 other listings on The Stack
- Python — in 1142 other listings on The Stack
- PyTorch — in 87 other listings on The Stack
- TensorFlow — in 53 other listings on The Stack
- Scikit-learn — in 24 other listings on The Stack
- Geometric Data
- Surface Reconstruction
- Linear Algebra
- Optimization
- C++
- Open3D
- GPU Programming
- Neural Representations
On The Stack (as of 2026-11-01)
Frequently asked questions about NavVis
Is this Lead Machine Learning Engineer - Geometric Spatial AI (F/M/D) role still open?
It was posted on 2026-10-30 and is listed as active on The Stack. Confirm on NavVis's application page before applying.
Does NavVis offer visa sponsorship?
This listing is marked as offering visa sponsorship. Eligibility rules are set by the employer, so check the details on NavVis's site.
Where is this role located?
The listing gives the location as Munich, Germany. It is marked hybrid.
What skills does this role ask for?
The listing names: Machine Learning, Deep Learning, 3D Point Cloud Processing, Computer Vision, Python, PyTorch, TensorFlow, Scikit-learn, Geometric Data, Surface Reconstruction, Linear Algebra, Optimization, C++, Open3D, GPU Programming, Neural Representations.