Job Details
Johns Hopkins, founded in 1876, is America's first research university and home to nine world-class academic divisions working together as one university.
IT@JH Research Computing is seeking a HPC Scientific Software Engineer to support faculty, researchers, and students engaged in high-performance and AI-driven research across Johns Hopkins University. The position is responsible for deploying, optimizing, and maintaining scientific software and computational workflows on advanced HPC Systems and related infrastructure.
Specific Duties & Responsibilities
- Software Deployment and Design (15%)
- Develop and refine deployment strategies for scientific software on HPC and AI systems.
- Design computational workflows, selecting optimal software configurations, and utilizing tools like Ansible for automation.
- Performance Optimization (20%)
- Analyze and optimize the performance of AI models and HPC applications, focusing on GPU-enabled computing.
- Integration and Optimization (15%)
- Develop, debug, and maintain software tools, libraries, and frameworks supporting HPC and AI workloads.
- HPC Scientific Software Support (30%)
- Manage and support scientific software deployment across HPC, cloud-based, and colocation facilities.
- Collaboration and Mentorship (5%)
- Work closely with cross-functional teams, including researchers, data scientists, and software developers.
- Technical Support and Training Workshops and Troubleshooting (15%)
- Resolve complex technical issues and perform root cause analysis for HPC/AI software challenges.
- Learning and Development (5%)
- Stay current with advances in HPC and AI technologies and methodologies.
- Container Orchestration (5%)
- Develop and manage container orchestration strategies to ensure scalability, reliability, and security of applications.
- Documentation and Compliance (5%)
- Create comprehensive documentation for system designs, performance metrics, and project status.
Other duties as assigned.
Minimum Qualifications
- 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.
Preferred Qualifications
- PhD in a quantitative discipline, such as Computer Science Engineering, Physics, Bioinformatics, or related fields, with advanced training in scientific computing.
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