Overview
**METAKI **Dresden, Germany (TU Dresden) | On-site / Hybrid | Co-Founder / Equity | Deep Tech / AI for Engineering **About Metaki **Metaki is building a 'Large Engineering Model' (LEM): a graph-neural-network surrogate trained on large-scale finite element simulation (FEA) data that predicts, near-instantly, how complex 3D parts respond to different materials, loads and boundary conditions — r
Full job description
**METAKI **Dresden, Germany (TU Dresden) | On-site / Hybrid | Co-Founder / Equity | Deep Tech / AI for Engineering **About Metaki **Metaki is building a 'Large Engineering Model' (LEM): a graph-neural-network surrogate trained on large-scale finite element simulation (FEA) data that predicts, near-instantly, how complex 3D parts respond to different materials, loads and boundary conditions — replacing slow FEA runs. The initial focus is solid and structural mechanics, with the long-term ambition of a general foundation model for engineering physics. **The opportunity **Founded by Samir El Masri (Founder, ongoing PhD in FEM, 3 years of industry experience in FEM & AI/ML for engineering), Metaki already has a working FEM → data → NN pipeline, is building out a large 3D training dataset, and is running training alongside early industry discussions. What's missing is a technical co-founder to help scale the modeling and engineering work while Samir also drives funding applications and industrial pilot partnerships. Tasks **What you will own ** **Model & platform development **- Co-own the neural-network surrogate modeling pipeline (FEM data → GNN training → fast inference), extending it from solid/structural mechanics towards a general engineering-physics foundation model.
- Scale the large 3D simulation dataset and physics-informed training infrastructure currently in development. **Technical leadership **- Take technical/CTO ownership alongside Samir El Masri (Founder), covering architecture, ML engineering and data pipeline decisions.
- Help turn early industry discussions into validated industrial pilots by making the model production-ready. **Fundraising support **- Support funding applications and strategic introductions with a credible technical narrative and roadmap. Requirements **What you bring ** **Core experience **- Strong machine learning background, ideally with graph neural networks, surrogate modeling, or physics-informed ML.
- Comfort working with finite element simulation data and engineering/physics domain concepts (solid or structural mechanics a plus). **Especially valuable **- Software/ML engineering experience taking a research pipeline to a scalable, production-ready product.
- Interest in building toward a general foundation model for engineering physics.
- Experience with industrial pilot partnerships or applied research collaborations. Benefits **Why join Metaki **- A working FEM → data → NN pipeline already built, not just an idea — real technical traction to build on.
- Early industry discussions already underway, with funding applications and pilot partnerships actively being pursued.
- Ground-floor technical co-founder equity in a company aiming to become a foundational-model platform for engineering physics. Metaki welcomes co-founder candidates regardless of gender, age, ethnic origin, religion or belief, disability, sexual identity, or any other characteristic. This is a search for the right partner to build the company with, not a conventional hire. Find Jobs in Germany on Arbeitnow
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