
Neural Concept accelerates engineering product development by embedding 3D deep learning models into design and simulation workflows to cut development time and improve performance. The platform uses…

Neural Concept accelerates engineering product development by embedding 3D deep learning models into design and simulation workflows to cut development time and improve performance. The platform uses…
What they do: 3D physics-aware deep learning platform to accelerate engineering product design and optimization
Founded: 2018 (EPFL spinout, Lausanne, Switzerland)
Customers: Works with major OEMs and tier-1 suppliers (industrial and automotive collaborations)
Recent funding: Reported $27M Series B (June 2024)
Simulation-driven product design and engineering R&D acceleration
2018
Software Development
9.1M
Series A reported as $9.1M led by Alven with participation from Aster, CNB and HTGF
27M
Series B reported at $27M with participation from D.E. Shaw, Alven, CNB (Constantia New Business), HTGF and Aster
| Company |
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Location
Lausanne
Employment Type
Full time
Location Type
Hybrid
Department
Vertical Solutions
About the role
Neural Concept’s Vertical Solutions team turns the most common engineering use cases into streamlined, production-grade workflows empowered by leading AI technologies. As a CAE Engineer, you’ll shape multi-fidelity simulation models and automation tailored to specific industry applications. You’ll operate in a cross-functional unit to move from one-off analyses to robust, repeatable solutions including best practices, APIs, and benchmarks that scale across projects. You’ll assist in translating customer problems into meshing playbooks, solver configurations, and KPIs, then harden them into automated pipelines that integrate with our platform and with customer toolchains.
What you will do
Build, validate, and maintain multi-fidelity simulation models; tune the accuracy/speed trade-off and best-practice settings for versatile purposes.
Calibrate models against benchmarks or test data; document assumptions, limitations, and verification steps.
Who you are
You get
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Automate full CAE pipelines: CAD preparation, meshing, solver setup, job submission/monitoring, post-processing, and visualization.
Contribute to lightweight APIs for launching studies and retrieving results at scale.
Run and optimize simulations on HPC/Cloud environments and leverage GPU acceleration where applicable.
Work with software engineers to integrate CAE solutions into data pipelines and the core product.
Partner with ML Engineers to expose parameters, metrics, and artifacts for analysis and iteration.
Strong simulation background in electro-magnetics applied to engineered systems. Additional experience in CFD, heat transfer, and/or FEA is a significant plus.
Experience with end-to-end simulation workflows across CAD Meshing Solving Post-processing Visualization.
Proficiency with commercial CAE software (e.g., Ansys suite, Ansys Motor-CAD, JMAG, or equivalent).
Scripting/programming: Python (required); also valuable: C++, Java/C#.
Exposure to open-source tools (e.g., OpenFOAM, FEniCSx) and pre/post tools (e.g., Gmsh, ParaView).
Strong written and verbal communication skills in English.
Hands-on practice running workloads on Cloud/HPC; familiarity with batch scheduling and job orchestration is a strong plus.
Experience building automation with commercial solver APIs or macros (e.g., PyAnsys, JMAG scripting) is a strong plus.
Comfort with Git and modern dev environments/IDEs; basic CI for validation of templates/scripts is a strong plus.