Software Engineer - Platform & DevOps

About NPco

Engineering progress is constrained by the speed of simulation. In aerospace, energy, and other safety-critical industries, design cycles are still governed by solvers built for a different era, accurate, but slow and costly, and fundamentally incompatible with real-time decision-making. NPco exists to change that constraint.

Founded by Emmanuel and Matthieu, both former researchers at France's national institute for research in digital science and technology (Inria) working on AI powered simulation, NPco is building foundational AI models for physical simulation. By combining advances in large-scale model architectures with modern compute, we enable real-time iteration across fluid dynamics, structural mechanics, and electromagnetics, without sacrificing physical fidelity.

We want to push engineering towards real time feedback loops. We want Aircraft components to be optimized aerodynamically in real time. Wind farm layouts to be explored interactively to maximize energy yield. Thermal stress in nuclear infrastructure to be anticipated before it becomes a limiting factor. These will come as the natural consequence of the faster physics simulation we are building.

We are deeply embedded in the European research ecosystem, backed by engineers and founders from organizations including Mistral AI, Dataiku, and DeepMind. As we scale our technology into real-world industrial deployments, we are looking for engineers who want to work at the boundary between frontier AI and the most demanding physical systems on earth. We want to become the new technology layer of modern engineering. Our ambition is global, our first office is in Paris, France.

Your Mission

As a Software Engineer, you will build the software infrastructure around our AI models. Your goal is to transform our pre-trained models into robust industrial tools, making NPco’s technology usable, seamless, and secure for our clients' engineers.

Infrastructure & Deployment: Build and define hybrid deployment pipelines (GCP Cloud and secure on-premise) tailored to the critical confidentiality constraints of our industrial clients.

Back-end Architecture: Develop the API and inference engine to ensure near-instantaneous response times on complex computational meshes.

Integration & Plugins: Design and develop connectors (plugins) to interface our models with industry standards (Ansys, Catia, Paraview).

3D Visualization: Implement mesh processing and visualization tools (based on VTK/WebGPU) to allow engineers to analyze results instantly.

Team Building: As a founding member of the tech team, you will actively participate in defining profiles, interviewing, and recruiting our future developers.

Technical Background: Advanced proficiency in Python with significant experience in software development, ideally within a B2B SaaS or scientific software context.

Versatility: You are comfortable and capable of moving from developing a desktop plugin to managing a Cloud API or optimizing Docker containers.

Rigor & Security: You understand the high stakes of industrial intellectual property and know how to write code that is exceptionally robust and secure.

Engineering Mindset: You have a strong affinity for physics, mathematics, or 3D environments. Understanding what a mesh or a boundary condition is represents a major plus.

Indicative Tech Stack: Python, PyTorch, VTK, Docker, Google Cloud, REST/gRPC APIs.

Culture: Small team of committed top scientists and engineers in their field.

High Impact: Join a founding team where your work directly shapes the product and its deployment with global leaders.

Work on physical AI that delivers immediate, real-world value, making planes, windfarms, and nuclear plants more efficient and sustainable.

Frontier AI: Work at the intersection of Generative AI, High-Performance Computing, and complex physics.

Direct Influence: As one of our first Engineers, you will have a massive say in our roadmap and how our user interface evolves to meet engineering needs.

Momentum: Join us at a key turning point as we scale from technical validation to major commercial expansion.

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