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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | 30 days ago
Internal Number: 25560 LEAD RESEARCH SOFTWARE ENGINEER, PORTABLE AI PERFORMANCE ENGINEERING, MA Green High Performance Computing Center, to be a hands-on research software engineering professional and serve
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 1 month ago
Posting Description LEAD RESEARCH SOFTWARE ENGINEER, PORTABLE AI PERFORMANCE ENGINEERING, MA Green High Performance Computing Center, to be a hands-on research software engineering professional and
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at least two related publications. Proficiency with core HPC programming languages and paradigms, including C/C++, Fortran, and MPI. Proficiency in GPU-accelerated HPC programming, with emphasis on CUDA and
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members of the group help each other. Opportunity for growth as a software developer in areas such as CUDA programming, analysis of neural data, machine learning model applications, and real-time
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potential use of Rust, CUDA, C/C++, Bash/Zsh, and Haskell while collaborating closely with students, professionals, and external partners. The role offers significant opportunities to contribute to system
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at sites all over the world. To strengthen the MPIfR Backend Development Group (BDG), we are looking for a Software Engineer (m/f/d). The BDG develops and operates high-performance, software-based data
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continuous learning and cultivates an environment where all members of the group help each other. Opportunity for growth as a software developer in areas such as CUDA programming, analysis of neural data
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include: Assist in porting quantum computing optimization codes to CUDA-Q for use with NVIDIA GPUs. Collaborate with NLR researchers on developing formulations and algorithms for solving optimization under
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). Experience with shared and distributed memory parallel programming models such as OpenMP and MPI. Experience with one more GPU or performance portability programming language (e.g., CUDA, HIP, Kokkos, SYCL
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environments. * Experience with parallel programming models, such as MPI, OpenMP, CUDA, or related technologies. * Experience compiling, porting, debugging, and optimizing scientific or engineering applications