Simulation Platform & ML Engineer

Turn cutting-edge simulation and ML research into software that engineers can actually use. At GREEN14, we are building simulation technology for complex industrial processes. Our team combines multiphysics models, machine learning and experimental data to understand systems such as plasma reactors and high-temperature metallurgical processes. We can build sophisticated models and fast surrogates. Now we want to turn that capability into robust software that can be used beyond our own research environment. WHAT WE ARE BUILDING GREEN14 started five years ago with a mission to develop emission-free production of critical raw materials using hydrogen plasma. Today, we operate a full-scale plasma reactor in Stockholm. Alongside it, we have built capabilities in multiphysics simulation, AI and surrogate modelling. Our ambition is to connect experiments, physics, simulation, surrogate models and optimization into a continuous learning process. But a great model sitting in a research notebook is not a product. Models need data and pipelines. Experiments need to be reproducible. Software needs APIs. Models need to be tested and versioned. Computation needs to be fast and reliable. That is where you come in. YOUR ROLE You will build the software and computational infrastructure connecting our physics, AI and experimental data. You will work directly with scientists and engineers developing our models and turn research code into software other engineers can reliably use. A typical problem might start with JAX code developed by a researcher. Your job is to ask: How do we make this reliable, testable, reproducible, fast and usable by someone who did not write it? You will have substantial ownership over the technical foundations of our simulation platform. WHAT YOU WILL DO Build backend architectures connecting sensor data, physics models, ML models and simulation workflows. Turn JAX-based research code into maintainable, production-ready software. Build pipelines connecti