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  • **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.

    Application form

    Apply for the job by filling the job application form with your details

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