Asks for

The ad says“5-7+ years of hands-on experience applying machine learning and deep learning to point cloud processing, filtering, registration, or surface reconstruction, with a strong theoretical grounding in the underlying methods”
The ad says“Familiarity with point cloud-specific deep learning architectures, for example PointNet++, sparse convolutional networks, graph neural networks, or transformer- and diffusion-based 3D models”
The ad says“5-7+ years of hands-on experience applying machine learning and deep learning to point cloud processing, filtering, registration, or surface reconstruction, with a strong theoretical grounding in the underlying methods”
The ad says“Familiarity with point cloud-specific deep learning architectures, for example PointNet++, sparse convolutional networks, graph neural networks, or transformer- and diffusion-based 3D models”
The ad says“Solid foundation in the mathematics of geometry, linear algebra, and optimization”
The ad says“5-7+ years of hands-on experience applying machine learning and deep learning to point cloud processing, filtering, registration, or surface reconstruction, with a strong theoretical grounding in the underlying methods”
The ad says“Solid foundation in the mathematics of geometry, linear algebra, and optimization”
The ad says“5-7+ years of hands-on experience applying machine learning and deep learning to point cloud processing, filtering, registration, or surface reconstruction, with a strong theoretical grounding in the underlying methods”
The ad says“Familiarity with point cloud-specific deep learning architectures, for example PointNet++, sparse convolutional networks, graph neural networks, or transformer- and diffusion-based 3D models”
The ad says“Strong Python skills for writing efficient, maintainable code, and hands-on experience with libraries such as PyTorch, TensorFlow, and Scikit-learn”
The ad says“Strong Python skills for writing efficient, maintainable code, and hands-on experience with libraries such as PyTorch, TensorFlow, and Scikit-learn”
The ad says“5-7+ years of hands-on experience applying machine learning and deep learning to point cloud processing, filtering, registration, or surface reconstruction, with a strong theoretical grounding in the underlying methods”
The ad says“Strong Python skills for writing efficient, maintainable code, and hands-on experience with libraries such as PyTorch, TensorFlow, and Scikit-learn”
The ad says“Familiarity with point cloud-specific deep learning architectures, for example PointNet++, sparse convolutional networks, graph neural networks, or transformer- and diffusion-based 3D models”
The ad says“5-7+ years of hands-on experience applying machine learning and deep learning to point cloud processing, filtering, registration, or surface reconstruction, with a strong theoretical grounding in the underlying methods”
The ad says“Strong Python skills for writing efficient, maintainable code, and hands-on experience with libraries such as PyTorch, TensorFlow, and Scikit-learn”
The ad says“Familiarity with point cloud-specific deep learning architectures, for example PointNet++, sparse convolutional networks, graph neural networks, or transformer- and diffusion-based 3D models”

Values

The ad says“Experience with C++ and 3D libraries such as Open3D, PyTorch3D, PCL, or CGAL”
The ad says“Experience with C++ and 3D libraries such as Open3D, PyTorch3D, PCL, or CGAL”
The ad says“Experience with computer graphics and GPU programming (CUDA, ROCm, or OpenCL)”
The ad says“Experience with computer graphics and GPU programming (CUDA, ROCm, or OpenCL)”
The ad says“Familiarity with ML experimentation and orchestration tooling, for example MLflow, Ray, Databricks, Slurm, or Weights and Biases”
The ad says“Experience with neural 3D representations such as NeRF, Gaussian splatting, or signed distance functions”
The ad says“Experience with computer graphics and GPU programming (CUDA, ROCm, or OpenCL)”
The ad says“Experience with Linux”
The ad says“Familiarity with ML experimentation and orchestration tooling, for example MLflow, Ray, Databricks, Slurm, or Weights and Biases”
The ad says“Experience with neural 3D representations such as NeRF, Gaussian splatting, or signed distance functions”
The ad says“Experience with C++ and 3D libraries such as Open3D, PyTorch3D, PCL, or CGAL”
The ad says“Experience with computer graphics and GPU programming (CUDA, ROCm, or OpenCL)”
The ad says“Experience with C++ and 3D libraries such as Open3D, PyTorch3D, PCL, or CGAL”
The ad says“Experience with C++ and 3D libraries such as Open3D, PyTorch3D, PCL, or CGAL”
The ad says“Familiarity with ML experimentation and orchestration tooling, for example MLflow, Ray, Databricks, Slurm, or Weights and Biases”
The ad says“Experience with computer graphics and GPU programming (CUDA, ROCm, or OpenCL)”
The ad says“Experience with neural 3D representations such as NeRF, Gaussian splatting, or signed distance functions”
The ad says“Familiarity with ML experimentation and orchestration tooling, for example MLflow, Ray, Databricks, Slurm, or Weights and Biases”
The ad says“Familiarity with ML experimentation and orchestration tooling, for example MLflow, Ray, Databricks, Slurm, or Weights and Biases”

OUR VISION

When people use our technology to "bridge the gap" between the physical and digital worlds, they don’t just capture reality - they create a new one. In this new reality, they are smarter, more productive, more streamlined, and more creative - because they have the digital foundation to build the world they want to live in.

That’s what NavVis offers in all our products and services: the tools to not just map the world as it is, but to pave the way to a better future. To forge something new. Physical or digital, there is only one reality. And it’s the reality NavVis empowers people to build better.

THE OPPORTUNITY

At NavVis, we build spatial intelligence technology that depends on high-quality 3D data. This is a machine learning engineering role focused on 3D geometric data. We're looking for an experienced engineer to develop and deploy machine learning models that operate on point clouds and 3D reconstructions, while raising the team's expertise in applying ML and DL to 3D data and broadening how the team uses it.

You'll work closely with cross-functional teams, including AI researchers, software engineers, and product designers, to build and ship models for 3D point cloud processing, filtering, surface reconstruction, and computational geometry. Most of your time goes into moving these methods from research into production, not just exploring them.

If you have practical experience and a strong theoretical grounding in cutting-edge machine learning and deep learning techniques, and want to apply them to 3D geometric data, you'll have the scope to shape how NavVis approaches 3D machine learning.

HOW YOU WILL MAKE AN IMPACT

Design and optimize machine learning and deep learning models for 3D point cloud data, covering filtering, denoising, registration, and surface reconstruction
Own 3D data pipelines end-to-end, from preprocessing and augmentation to model adaptation and evaluation against ground-truth geometry
Integrate 3D ML solutions into existing workflows and products by collaborating with other teams
Adapt state-of-the-art 3D deep learning methods for production use, for example point-based architectures such as PointNet++, sparse voxel or convolutional networks, graph neural networks, and implicit or neural representations
Build scalable, reproducible training pipelines for large 3D datasets
Improve model performance by analyzing results against geometric and perceptual quality metrics

WHAT WILL HELP YOU SUCCEED IN THE ROLE

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, with a strong theoretical grounding in the underlying methods
Familiarity with point cloud-specific deep learning architectures, for example PointNet++, sparse convolutional networks, graph neural networks, or transformer- and diffusion-based 3D models
Strong Python skills for writing efficient, maintainable code, and hands-on experience with libraries such as PyTorch, TensorFlow, and Scikit-learn
Solid foundation in the mathematics of geometry, linear algebra, and optimization
Fluent English communication skills, needed to collaborate with AI researchers, software engineers, and product designers

Would be an added benefit

Experience with computer graphics and GPU programming (CUDA, ROCm, or OpenCL)
Experience with neural 3D representations such as NeRF, Gaussian splatting, or signed distance functions
Familiarity with ML experimentation and orchestration tooling, for example MLflow, Ray, Databricks, Slurm, or Weights and Biases
Published research papers or open-sourced projects in a relevant ML/DL field
Experience with C++ and 3D libraries such as Open3D, PyTorch3D, PCL, or CGAL
Experience with Linux

HOW WE WILL KNOW WE ARE A PERFECT MATCH

Your recruiting partner for this role is Rina (she/her). You can expect to go through a screening call, and up to 4 rounds of interviews, where we would love to discover your passion and interests, introduce you to who we are and what drives us, and finally understand how we can potentially add value to each other's growth.

HOW WE WILL KEEP YOU SMILING

It's important to take a break from work! We offer 30 days of paid time off per year
Affordable access to a vast network of fitness and wellness facilities through EGYM Wellpass subsidy
Deutschlandticket subsidy to support sustainable travel using public transport
We offer flexible working hours and a hybrid work setup, enabling you to plan your work around your life, and not your life around work!
We offer full visa and relocation support for international candidates
An attractive bike leasing model through JobRad, in line with our commitment towards sustainable mobility
A competitive compensation package that values the skills and experience you bring
Up to 4000 EUR employee referral bonus
Financial support for local language classes to help you in your journey of integrating into the culture!

ABOUT US

NavVis is a technologically-focused, global leader in reality capture and digital factory solutions. Prominent manufacturers and laser scanning professionals around the world trust our ground-breaking technology, designed to capture and share the built environment as photorealistic digital twins. By bridging the physical and digital worlds, we’re helping organizations make smarter decisions and build more efficient, connected operations.

With over 300 people from around 60 nationalities and offices around the globe, we’re proud to be a truly international and diverse place to work. As a scaling company, we bring together the agility, innovation, and entrepreneurial mindset of a startup with the professionalism and reliability of an established enterprise — offering our team the best of both worlds.

You’ll be part of an open culture that values trust, collaboration, and transparency. We are proud of our environment where diverse talent can thrive and where feedback fosters individual growth and development. Do you share our passion for disruptive technology and want to be part of our dynamic journey? At NavVis, you’ll own your projects, bring innovative ideas to life, and have real opportunities to grow your career and be recognized for your impact.

We derive our strength from our diversity.

NavVis’ unwavering commitment to fostering an inclusive and diverse workplace has laid the foundation for our incredible growth. We thrive on the collective strength of our people who come from diverse backgrounds. We respect and value every experience associated with race, gender identity, sexual orientation, nationality, religion and disability. We do not discriminate on the basis of any of these, or other identities, and strongly encourage everyone to apply.

Together with you, we build NavVis!

If you need assistance at any stage of the recruiting process due to a disability, please reach out to your recruiting partner(s) for this position.