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HPC Scientific Software Engineer
JHU EEHPCHPC Scientific Software Engineer at IT@JH Research Computing supporting AI-driven research and optimizing workflows on advanced HPC Systems. Engaging in user support and long-term projects with interdisciplinary teams.
Core Competencies
Role fitUse this summary to align your resume positioning with the role.
Demonstrates expertise in deploying, optimizing, and maintaining scientific software and computational workflows on HPC systems, with a strong focus on AI-driven research and performance optimization. Proficient in managing complex software stacks and containerized applications while collaborating with interdisciplinary teams to enhance system performance.
ATS Keywords
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Tech Stack
Tools & technologiesAbout the role
Key responsibilities & impact- Support faculty, researchers, and students engaged in high-performance and AI-driven research.
- Deploy, optimize, and maintain scientific software and computational workflows on advanced HPC Systems and related infrastructure.
- Manage and troubleshoot complex software stacks, containerized applications, and GPU-accelerated workloads using tools such as SLURM, Easy build, Spack, etc.
- Collaborate closely with interdisciplinary research groups to enhance system performance, streamline data-intensive workflows, and integrate cutting-edge technologies.
- Analyze and optimize the performance of AI models and HPC applications, focusing on GPU-enabled computing.
- Implement parallel processing, distributed computing, and resource management techniques for efficient job execution.
- Develop, debug, and maintain software tools, libraries, and frameworks supporting HPC and AI workloads.
- Manage and support scientific software deployment across HPC, cloud-based, and colocation facilities.
Requirements
What you’ll need- Master’s degree in computer science or a closely related quantitative discipline.
- Five years of experience in HPC user support, software deployment, and performance optimization within an academic or research environment.
- Experience in scientific computing environments and applications.
- Hands-on experience with SLURM, for job scheduling.
- Proficiency in Python, Perl, C/C++, and Shell scripting for automation and system management.
- Advanced knowledge of Linux systems and proficiency in scripting languages such as Python, Perl, and Shell.
- Familiarity with scientific application management tools such as Containerization, LUA modules, CMake, Spack, and EasyBuild.
- Training Workshops, Performance Optimization and Troubleshooting.
Benefits
Comp & perks- Total rewards package that supports our employees' health, life, career and retirement.