Artificial Intelligence Engineer

Location: Europe

Working Model: Remote / Flexible within Europe

Our client is building a new generation of AI-enabled engineering software combining artificial intelligence, computational geometry, CAE and physics-based engineering technologies.

The company is looking for a highly experienced AI Software Engineer specialising in multimodal models for 3D geometry, CAD and mesh representations .

This is a hands-on software and algorithm development role focused on building production-grade AI technologies capable of understanding, representing and generating complex engineering geometry.

The successful candidate will work at the intersection of multimodal foundation models, geometric deep learning, CAD/CAE geometry, mesh representations and engineering software development .

• Design and develop multimodal AI models capable of understanding and processing engineering geometry.
• B-Rep / boundary representations
• surface and volume meshes
• point clouds
• images and sketches
• text and engineering metadata
• simulation and physics data
• Develop scalable representations and embeddings for complex 3D engineering geometry.
• Develop geometry encoders and tokenisation strategies suitable for large-scale multimodal models.
• Develop transformer, graph-based, generative or foundation-model architectures for 3D engineering data.
• Develop models for geometry understanding, generation, reconstruction, modification and reasoning.
• Develop AI capabilities for mesh generation, mesh understanding and geometry-to-mesh workflows.
• Integrate AI models into production engineering software products and CAE/CAD workflows.
• Develop robust training, inference and evaluation pipelines.
• Optimise models for large engineering datasets and production deployment.
• Work closely with computational geometry, CAE, meshing and HPC software teams.
• Translate state-of-the-art AI research into reliable and scalable industrial software.
• Contribute to technical architecture and long-term product strategy for geometry-based AI technologies.

• MSc or PhD in Computer Science, Artificial Intelligence, Machine Learning, Computational Geometry, Applied Mathematics or a related discipline.
• Strong hands-on software development experience in AI/ML.
• Excellent programming skills in Python , with strong software engineering fundamentals.
• Experience with PyTorch or another major deep learning framework.
• Strong experience in one or more of the following:
• transformers
• geometric deep learning
• 3D machine learning
• representation learning
• Experience working with 3D data such as meshes, CAD geometry, B-Rep, point clouds or surface representations.
• Strong understanding of modern deep learning architectures and model training methodologies.
• Ability to translate research concepts into robust production software.

• Experience with CAD, CAE or engineering geometry .
• Knowledge of B-Rep / boundary representation, NURBS or parametric CAD.
• Experience with triangle meshes, tetrahedral meshes, surface meshes or unstructured meshes.
• Experience with geometric deep learning or graph neural networks.
• Experience developing transformer architectures for 3D or geometric data.
• Experience with multimodal foundation models involving text, images and 3D representations.
• Experience with diffusion models, autoregressive models, VQ-VAE or other generative architectures.
• Experience with neural operators, Physics AI or simulation-based machine learning.
• Experience with geometry generation or AI-driven meshing.
• Experience developing commercial engineering, CAD, CAE or scientific software.
• Strong C++ skills would be advantageous.
• Experience optimising large models for GPU inference or distributed training would be beneficial.

Relevant experience may include:

• Geometric deep learning
• Generative CAD
• Mesh generation with deep learning
• 3D representation learning
• Vision-language models applied to engineering data
• Graph transformers
• Mesh transformers
• Point-cloud transformers
• B-Rep learning
• Physics-informed or physics-aware AI

We are particularly interested in candidates who combine strong AI development capabilities with an understanding of ge