HPC Applications Engineer
Helsing
| Company | Helsing |
| Category | Engineering |
| Location | Munich |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 1 Jun 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (greenhouse) |
Description
Who we are
Helsing is a defence AI company. Our mission is to protect our democracies. We aim to achieve technological leadership, so that open societies can continue to make sovereign decisions and control their ethical standards.
As democracies, we believe we have a special responsibility to be thoughtful about the development and deployment of powerful technologies like AI. We take this responsibility seriously.
We are an ambitious and committed team of engineers, AI specialists and customer-facing programme managers. We are looking for mission-driven people to join our European teams – and apply their skills to solve the most complex and impactful problems. We embrace an open and transparent culture that welcomes healthy debates on the use of technology in defence, its benefits, and its ethical implications.
The role
Helsing operates on-premises high-performance computing (HPC) infrastructure supporting electromagnetics, computational fluid dynamics, and multi-physics simulation. As an HPC Applications Engineer, you will manage the simulation workflow layer built on top of this cluster. You will ensure the solver application stack is reliable, fast to set up, and easy to iterate on, allowing simulation engineers to remain highly productive. Working closely with the HPC infrastructure team, you will build automated end-to-end pipelines, manage results traceability, and serve as the primary technical partner to engineers. The role is based on-site in Munich, with regular travel to our Tussenhausen site.
The day-to-day
Manage the simulation software stack from installation and configuration to version management across solver releases
Administer licence servers, monitor utilisation across teams, and engage with vendors to resolve support cases efficiently
Benchmark solver scaling and tune core counts, memory configuration, and MPI settings to optimise application performance
Develop parameterised, end-to-end simulation pipelines that automate geometry preparation, meshing, solver execution, and post-processing
Implement and maintain a results database for rapid retrieval of past simulations and enforce data archival policies aligned with aerospace certification
Build dashboards for job status visibility and develop tooling for engineers to query and compare simulation results
Partner with simulation engineers to troubleshoot jobs, resolve blockers, and gather feedback to improve pipeline reliability
Ensure the platform meets solver and workflow requirements through close collaboration with the HPC infrastructure team
You should apply if you
Demonstrate practical capability working with CAE or simulation tools within a production HPC environment
Possess hands-on capability in at least one core simulation discipline, such as CFD, FEA, electromagnetics, aeroelasticity, or multi-physics
Build and maintain automated simulation pipelines, encompassing job chaining, parameterisation, and pre/post-processing automation
Write robust scripts using Python and Bash, with an understanding of Java or Tcl for solver macro development
Submit and manage jobs using HPC schedulers such as Slurm or PBS Pro, demonstrating a practical understanding of MPI parallel execution
Note: We operate in an industry where women, as well as other minority groups, are systematically under-represented. We encourage you to apply even if you don’t meet all the listed qualifications; ability and impact cannot be summarised in a few bullet points.
Nice to Have
Navigate high-cadence simulation environments such as motorsport, aerospace OEM, or defence
Utilise Altair or Siemens simulation suites in production scenarios
Create CAD-to-mesh workflows using tools such as HyperWorks, ANSA, or Pointwise
Integrate workflows with simulation data management systems or PLM architecture
Apply optimisation frameworks including design of experi
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