Machine Learning Engineer (m/f/d)

Focused·Darmstadt, DEmid

In short

→Ingeniero de ML que combina inteligencia artificial con física computacional para acelerar fusiones láser.
→Diseña modelos de aprendizaje automático que optimizan simulaciones complejas y sistemas físicos en tiempo real.
→Destaca por integrar IA con simulaciones de alta fidelidad en un entorno de fusión nuclear de vanguardia.

Fluency in English required for collaboration with international teams.

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What they ask for

✓Master o PhD en ML, Física Computacional, Matemáticas Aplicadas, Ciencia de Datos o campo relacionado.
✓Experiencia comprobada en modelos de ML para sistemas físicos complejos con deep learning (PyTorch, TensorFlow/JAX).
✓Dominio avanzado de Python; conocimientos en C++ o Fortran y entornos HPC (MPI/OpenMP, schedulers).
✓Experiencia práctica con modelos reducidos (ROMs), surrogates, GP, redes neuronales y cuantificación de incertidumbre.
✓Habilidades en PDEs, datos en serie temporal y espacios de parámetros multidimensionales.
✓Experiencia con simulaciones multiphísicas (COMSOL, ANSYS, solvers personalizados) y datos de sensores reales.

Don't tick every box? That's normal — your free dossier shows your gaps and how to cover them in the interview.

PyTorchTensorFlowJAXGaussian ProcessesNeural NetworksReduced-Order ModelsPhysics-Informed MLPINNsBayesian OptimizationActive Learning

Who should you write to at Focused?

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Focused Energy is building the future of clean energy through laser-driven inertial fusion. Backed by our $240M Series A — the largest fully secured Series A in the global fusion industry — we are scaling rapidly across multiple geographies. Based in Germany and the US, we have brought together the top scientific and engineering minds using proven technologies to unlock fusion power at commercial scale. Focused Energy is working to realize game-changing scientific innovation that promises to deliver a clean, sustainable and abundant source of power globally. Your Role This role sits at the intersection of ML engineering and computational physics, working within our Software Engineering & Digital Twin environments. You'll collaborate closely with optical engineers, laser and fusion physicists, simulation scientists, and systems engineers to embed data-driven intelligence directly into our Digital Twin architecture. You’ll be reducing design risk, shortening development timelines, and unlocking system-level optimization that purely physics-based approaches can't achieve at the speed we need. You will design, build, and deploy machine learning models that enhance, accelerate, and augment our multiphysics simulation environments across our high-energy laser systems, target injection and tracking system, target manufacturing system, and fusion chamber. This will enable faster design cycles, predictive system optimization, and real-time decision support across our laser, targetry, and fusion programs.

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