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SiemensPlace(s)
NürnbergHPC/Parallel/C++ - Software Engineer (m/f/d) - SISW, Nuernberg
Permanent
IT, telecommunications, computer science
Offer archived at 08/01/2020
Siemens
Premier groupe européen de haute technologie, Siemens conjugue depuis toujours performance technique, innovation, qualité et fiabilité.
Nos activités centrées sur les secteurs des infrastructures et des villes, l'industrie, l'énergie et la santé, ciblent des marchés de croissance sur lesquels le Groupe nourrit l'ambition d'être leader.
Missions
- The position reports to the HPC program manager, as part of the Simulation Frame-work division of the STAR-CCM+ Platform department.
- Design, implement, and extend HPC-specific framework for use on a range of systems and modern hardware
- Interact with stakeholders to identify needs and requirements
- Profile and optimize new and existing implementations to ensure scalability on shared and distributed memory systems
- Collaborate closely as part of a large, distributed team of developers, testers, and managers
- Participate in peer-based code and design reviews
- Communicate project status during regular meetings
- Use systems for managing development including Jira, Confluence, Git, and BitBucket
Your qualifications
- Master’s Degree or higher in a related field (computer science, applied mathematics, or engineering)
- At least 3 years of professional software development experience in a related field
- Expertise in C++ and object-oriented software development
- Experience with designing/implementing distributed parallel algorithms via message passing (e.g., MPI)
- Experience with shared memory (threads) and instruction level (SIMD) parallelism
- Proficiency at optimizing and benchmarking code for performance and memory
- A sound understanding of algorithmic complexity
- Experience working on large, distributed teams and navigating large, complex code bases
- Experience with software development tool-chains (Git, Eclipse, Visual Studio, etc.)
- Ability to communicate complex technical issues clearly and to present data concisely
- Ability to handle multiple tasks with minimal oversight
- Familiarity with computational simulation such as CFD and FEA
- Practical experience with vectorization, SIMD, and GPGPU programming
- Experience with graph partitioning and associated tools (e.g.,ParMETIS)
- Experience with parallel file systems (e.g., Lustre, Panasas)
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Offer archived at 08/01/2020