HPC Scientific Software Engineer

Job not on LinkedIn

🕒 July 27

🦀 Maryland – Remote

🦀 Maryland – Remote

💵 $85.5k - $149.8k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🧑‍💻 Full-stack Engineer

👻 Ghost score 42%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

JHU EEHPC

WebsiteLinkedInAll Job Openings

11 - 50 employees

📚 Education

🤖 Artificial Intelligence

🏥 Healthcare

Education • Artificial Intelligence • Healthcare

JHU EEHPC is the Energy Efficient High Performance Computing Lab at Johns Hopkins University, led by Tinoosh Mohsenin. The lab focuses on designing medical, health, and wearable devices and developing tiny, energy-efficient wearable and mobile computing systems through cross-layer approaches spanning algorithms, architecture, hardware, and system integration. It applies high-performance computing and artificial intelligence methods to smart health monitoring, robotics, autonomous navigation, and related domains, aiming to revolutionize healthcare, transportation, and public utilities.

📋 Description

• 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

• 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

• Total rewards package that supports our employees' health, life, career and retirement.