Simulation Platform & ML Engineer
Confirmed on the employer's own hiring board on Oct 14, 2026. First seen by Alion on Sep 17, 2026.
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 connecting experimental data, simulation, surrogates and optimization.
Develop infrastructure for model training, evaluation and reproducibility.
Build APIs, packages and repositories for long-term production use.
Establish testing, CI/CD, versioning and monitoring for scientific software.
Identify computational bottlenecks and improve performance.
Contribute to deployment and cloud infrastructure as our products mature.
WHO YOU ARE
You have experience taking technically complex software from prototype to something other people can reliably use.
You might come from software engineering, ML engineering, scientific computing or data engineering.
We are particularly interested in experience with:
Python and modern software engineering.
JAX or other numerical and ML frameworks.
Backend architectures and APIs.
Data pipelines and databases.
ML infrastructure and MLOps.
Testing, CI/CD and reproducible workflows.
Computationally intensive workloads.
Experience with Docker, cloud infrastructure, Kubernetes, GPU computing, FastAPI or ML tooling is useful. Experience with JAX, scientific computing or simulation software is particularly relevant.
We do not expect you to tick every box.
THE KIND OF PERSON WE ARE LOOKING FOR
You do not need to be a plasma physicist.
What matters is that you enjoy working at the boundary between scientific computing, machine learning and real-world software engineering.
You like understanding what researchers are trying to achieve, but your instinct is to turn clever prototypes into systems other people can depend on.
You care about architecture, performance and maintainability, but you also write code.
You should also be curious about the physical world behind the software. Our code represents real plasma, particles, materials and experiments.
WHY GREEN14
Many software engineers working in simulation never see the physical system their code represents.
Here, the reactor is downstairs.
Our engineers run experiments. Sensors generate data. Our simulation team compares results with models. The models improve. You build the infrastructure that makes that loop faster and more reliable.
Our ambition is broader than one reactor. We want to help engineers understand, optimize and scale complex high-temperature processes across industries.
HOW WE WORK
You will join a team of serious engineers and scientists who care about getting things right.
We are international, curious and direct. We challenge each other's thinking and change our minds when the data tells us to.
There is very little hierarchy. Good ideas matter more than titles.
We are ambitious, but low on ego. We work hard, flexibly, and value having a life outside work.
THE PRACTICAL STUFF
Compensation consists of salary and pension.
We are based at Sweden's leading technical university, close to central Stockholm and our plasma reactor.
If you want to turn physics, AI and experimental data into software that could change how industrial processes are developed and optimized, we would like to hear from you.
The position will remain open until we find the right person.