Primary technologies, domain competencies, and required qualifications
Verified specifications, primary responsibilities, and qualifications
**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.
**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.
**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.
**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.
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