GPU-Accelerated Scientific Software Engineer for Fusion

Marvel Fusion Inc.

United States

Remote

USD 101,000 - 141,000

Full time

11 days ago

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Benefits offered by this job

Public Transport Subsidy
Employee Incentive Program
Phone Bill Reimbursement
Wellpass or Health Insurance
Professional Learning & Development
Relocation Support
Company Pension Plan
30 Days Vacation
Modern Office in Munich Center
Healthy office snacks
Regular Team Events

Job summary

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.

Qualifications

  • A degree in Computer Science, Physics, Applied Mathematics, Engineering or a related field, or equivalent practical experience.
  • Strong Python software engineering skills and a track record of independently delivering maintainable software within an existing codebase.
  • Experience with scientific or numerical computing, including testing numerical accuracy and collaborating with domain experts.
  • Practical experience profiling computational workloads and using GPU computing frameworks such as CuPy, PyTorch, JAX or CUDA.
  • Hands-on experience deploying scientific Python or GPU workloads on remote Linux servers or cloud infrastructure, including reproducible environments, job execution and data handling.
  • A structured approach to debugging, version control, automated testing and documentation, with the ability to make pragmatic engineering decisions.
  • A self-driven, collaborative working style and excellent written and verbal communication skills in English.
  • Direct experience with AWS GPU services or shared NVIDIA GPU infrastructure, including containers, workload scheduling or monitoring.
  • Expertise in CUDA, multi-GPU computing, high-performance computing or performance-portable numerical software.
  • Experience integrating scientific applications with compute services, or a background in optics, photonics or experimental data analysis.
  • Experience evaluating AI-based acceleration of scientific workloads against accuracy and runtime benchmarks.

Responsibilities

  • 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.

Skills

Python software engineering
GPU computing
Profiling
English communication
Team collaboration
Problem solving

Education

Degree in Computer Science, Physics, Applied Mathematics, Engineering or related field

Tools

CuPy
PyTorch
JAX
CUDA

Job description

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.

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