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Marvel Fusion Inc. in Munich is seeking a computational software engineer to develop and maintain scientific Python software, collaborating with scientists to translate research into robust, reusable features.
You will profile workloads, optimize CPU/GPU performance, and deploy workloads on NVIDIA GPU servers or AWS, ensuring reproducible environments and automated workflows; join IT for access controls and monitoring.
Founded in 2019, Marvel Fusion is Europe’s leading fusion energy company, uniting 120 scientists, engineers, and entrepreneurs across our locations in Munich and Colorado. Backed by over €385 million in public and private funding, we’re driven by a shared mission: to deliver clean, abundant energy to the world.
Solving one of the most complex technological challenges known to humanity, harnessing Fusion on Earth Part of a highly purpose-driven team working on providing the world with clean, safe and abundant energy Working alongside world-leading scientists and entrepreneurs in the field of Fusion Part of a start-up where growth on a company and individual level is the default As part of our multidisciplinary research and engineering team, you will shape how we tackle computational challenges in fusion research. You will combine your software expertise with the team’s knowledge of physics and engineering to develop new approaches, make technical decisions and turn ideas into reliable scientific software. From advancing numerical performance to enabling shared GPU computing on NVIDIA servers or AWS, you will own meaningful technical challenges and contribute directly to our scientific progress. Develop and maintain scientific Python software, turning research requirements into reusable, tested features and clear interfaces. Work with scientists to define acceptance criteria and verify numerical results against reference cases and agreed accuracy requirements. Use profiling to identify bottlenecks; compare algorithms, code translations and CPU/GPU implementations through reproducible benchmarks. Prepare and deploy scientific workloads on NVIDIA GPU servers or AWS using reproducible environments and automated execution workflows. Work with IT to support multiple users through appropriate access controls, job scheduling, resource allocation, monitoring and result storage. Connect computational services to internal applications through stable APIs for job submission, status tracking and result retrieval. Improve testing, continuous integration, packaging and documentation, and independently carry agreed development tasks through to delivery.
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