AI Software Engineer (3D Geometry & Multimodals) - Europe Wide

A technology company developing advanced engineering software is creating a new generation of AI-powered tools that combine artificial intelligence, computational geometry, CAE and physics-based technologies.

It is seeking an accomplished AI Software Engineer to develop production-grade models capable of interpreting, representing and generating complex 3D engineering geometry.

This is a hands-on software and algorithm development position at the intersection of multimodal foundation models, geometric deep learning, CAD/CAE data and engineering software. You will turn innovative research into scalable technology for real industrial applications.

What you will be developing

• Multimodal AI models that understand and process engineering geometry.
• Representations combining CAD, B-Rep, meshes, point clouds, images, sketches, text, metadata and simulation data.
• Scalable embeddings, encoders and tokenisation strategies for complex 3D information.
• Transformer, graph-based, generative and foundation-model architectures for engineering data.
• Models for geometry generation, reconstruction, modification, understanding and reasoning.
• AI capabilities for mesh generation and geometry-to-mesh workflows.
• Reliable training, inference and evaluation pipelines.
• Models optimised for large engineering datasets and production deployment.
• AI technology integrated into commercial CAD, CAE and engineering software workflows.

You will collaborate with computational geometry, meshing, CAE and HPC specialists while contributing to the technical direction of the company’s geometry-based AI platform.

What you will bring

• An MSc or PhD in computer science, artificial intelligence, machine learning, computational geometry, applied mathematics or a related discipline.
• Strong hands-on AI or machine-learning software development experience.
• Excellent Python programming skills and solid software engineering fundamentals.
• Experience using PyTorch or another major deep-learning framework.
• Strong knowledge in at least one of the following areas:
• Multimodal learning
• Foundation models
• Transformers
• Generative models
• Geometric deep learning
• 3D machine learning
• Graph neural networks
• Representation learning
• Experience working with meshes, CAD geometry, B-Rep, point clouds or other 3D surface representations.
• A thorough understanding of modern model architectures and training techniques.
• The ability to translate research concepts into robust production software.

Particularly relevant experience

Additional experience could include:

• CAD, CAE or engineering geometry.
• B-Rep, NURBS or parametric CAD.
• Triangle, tetrahedral, surface or unstructured meshes.
• Transformer architectures for geometric or 3D data.
• Multimodal models combining text, images and 3D representations.
• Diffusion models, autoregressive models or VQ-VAEs.
• Neural operators, Physics AI or simulation-based machine learning.
• Generative CAD, geometry generation or AI-driven meshing.
• Graph, mesh or point-cloud transformers.
• Commercial engineering or scientific software development.
• C++ software engineering.
• GPU inference optimisation or distributed model training.

Your profile

This opportunity is particularly suited to an AI engineer who has worked directly with complex 3D engineering representations. Experience building models for meshes, CAD data, B-Rep geometry or point clouds will be especially relevant.

If you are excited by the opportunity to combine advanced AI with 3D geometry and real-world engineering software, apply now or email [email protected].