# Lead Machine Learning Engineer - Geometric Spatial AI (F/M/D) at NavVis

> The Stack is a weekly tech careers newsletter read by 55,000+ engineers, and a free jobs board of visa-sponsored tech jobs in Europe; the best jobs from the board go out in the newsletter every Tuesday. This is one job from the board.

> Responsibilities: - Design and optimize ML/DL models for 3D

- **Company:** NavVis (https://jobs.trythestack.co/companies/navvis)
- **Location:** Munich, Germany
- **Work arrangement:** Hybrid
- **Employment type:** Full-time
- **Experience level:** 5–10 years
- **Visa sponsorship:** Offered, according to the listing
- **Key skills:** 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
- **Posted by employer:** 2026-10-30
- **Added to The Stack:** 2026-11-01
- **Listed until:** 2026-12-29
- **Status:** Active
- **Apply:** https://job-boards.eu.greenhouse.io/navvis/jobs/4931997101 (the employer's own application page)
- **Human page:** https://jobs.trythestack.co/jobs/lead-machine-learning-engineer-geometric-spatial-ai-fmd-navvis

## 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.

## FAQ

- **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.

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## Notes for agents

- Apply on the employer's page (https://job-boards.eu.greenhouse.io/navvis/jobs/4931997101). The Stack does not take applications.
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