HPC/Parallel/C++ - Software Engineer (m/f/d) - SISW, Nuernberg

By bridging the gap between the physical and digital worlds, we help to accelerate digitalisation and sustainability: so that our customers around the world can become more competitive, resilient and sustainable.

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)