Gexcon

Bergen

We're looking for a Machine Learning Engineer to help us bring ML to industrial safety simulation.
Gexcon is a world leader in safety and risk management, best known for FLACS --- our industry-standard CFD software used to model gas dispersion, explosions, fires, and other consequence scenarios for clients across energy, process, and emerging industries. Founded in 1987 and headquartered in Bergen, we are around 200 employees operating globally from offices around the world.
CFD simulations are powerful but computationally expensive. A single high-fidelity FLACS run can take hours or days, which limits how often engineers can iterate on a design or explore a parameter space. We want to change that --- and we are looking for the person to help us do it.
This is an on-site position at our office in either Bergen or Trondheim.
Your mission will be to build machine learning models --- surrogate models, reduced-order models, and similar approaches --- that approximate the results of CFD simulations orders of magnitude faster than running the full physics.
This is a greenfield effort. You will have significant influence over the technical direction, the tooling, and how ML capabilities are integrated into our existing products and workflows.
What you will work on
<ul><li>
Designing and training physics-informed ML models on data generated from FLACS simulations
</li><li>
Building the data pipelines and tooling needed to turn CFD outputs into high-quality training data
</li><li>
Working closely with our CFD scientists and software engineers to validate models against physical ground truth
</li><li>
Deploying models into production so they can be used by customers and internal consultants
</li><li>
Helping define our long-term ML strategy as the discipline grows inside Gexcon
</li></ul>
Who we are looking for
We are open to candidates at very different career stages. The ideal profile combines machine learning experience with CFD or computational physics background --- but we know that combination is rare, so we are equally interested in strong candidates from either side.
You might be a fit if you have one or more of the following:
<ul><li>
Experience designing, training, and deploying machine learning models in a production or research setting
</li><li>
A background in CFD, computational physics, or a related engineering discipline, with ML experience
</li><li>
A strong software engineering background with the curiosity and aptitude to grow into ML systems
</li><li>
A recently completed degree (BSc, MSc, or PhD) in machine learning, computational science, physics, applied mathematics, computer science, or a related field
</li></ul>
We welcome both senior engineers who can shape the direction of this work and recent graduates who want to grow into the role. What matters most is technical curiosity, scientific rigor, and the ability to learn quickly. If you are unsure whether your background fits, we still encourage you to reach out. We would rather have the conversation than miss a good candidate.
What we offer
<ul><li>
The chance to apply ML to genuinely hard physical problems, with real-world safety impact
</li><li>
A collaborative environment alongside some of the world's leading CFD scientists and engineers
</li><li>
Greenfield scope --- your work will define how Gexcon does ML
</li><li>
Competitive Norwegian terms, including pension and a professional development budget
</li><li>
A long-term, stable employer with a clear product vision
</li></ul>

Do you want to make CFD simulations 1000x faster?