Inside Higher Ed · 1 week ago
HPC Sr. Scientific Software Engineer (IT@JH Research Computing)
Baltimore, MD
Full-time
Onsite
Mid, Senior Level
$100K/yr - $175K/yr
5+ years expInside Higher Ed is seeking an HPC Sr. Scientific Software Engineer to support research computing initiatives. The role involves developing and optimizing scientific software deployment strategies on HPC and AI systems, collaborating with cross-functional teams, and mentoring junior engineers.
Digital MediaEducationHigher EducationJournalismRecruiting
Responsibilities
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
Assist teams in implementing, tuning, and optimizing AI models and gateway applications (e.g., XDMoD, Coldfront, Open OnDemand, CryoSPARC Live, SBGrid, AI Agents)
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
Collaborate with the system team and software vendors (e.g., NVIDIA, Intel, Matlab) to optimize systems for maximum performance
Utilize CUDA, DNN, TensorRT, and Intel Compilers to enhance system performance
Manage and support scientific software deployment across HPC, cloud-based, and colocation facilities
Oversee installation, configuration, and maintenance of HPC packages with tools like CMake, Make, EasyBuild, Spack, and Lua module files
Work closely with cross-functional teams, including researchers, data scientists, and software developers, to address complex HPC/AI challenges
Mentor junior engineers and foster a culture of continuous learning
Resolve complex technical issues and perform root cause analysis for HPC/AI software challenges
Implement effective solutions to prevent recurrence and improve system reliability
Provide training workshops for researchers and students, focusing on troubleshooting, optimizing workflows, and effectively using HPC systems
Stay current with advances in HPC and AI technologies and methodologies
Incorporate new research findings into existing systems to improve performance and capabilities
Develop and manage container orchestration strategies to ensure scalability, reliability, and security of applications
Oversee the container lifecycle from creation and deployment to scaling and removal
Create comprehensive documentation for system designs, performance metrics, and project status
Ensure compliance with security and regulatory standards for all HPC and AI systems
Design, deploy, and maintain large-scale Linux HPC clusters with CPU/GPU resources, high-speed networks, and distributed storage
Develop and maintain automation frameworks for provisioning, monitoring, and software lifecycle management
Implement and optimize job scheduling, container orchestration, and workflow automation tools to support diverse research workloads
Collaborate with faculty and research teams to parallelize, containerize, and scale computational workflows for multi-GPU and distributed environments
Benchmark and tune application performance across architectures, documenting findings and sharing best practices
Integrate and support AI/ML frameworks, scientific libraries, and workflow engines (Snakemake, Nextflow, Dask, Ray)
Ensure system and application reliability through proactive monitoring (Prometheus, Grafana, ELK) and incident response participation
Support reproducibility and FAIR data principles through version-controlled, containerized environments
Contribute to documentation, training materials, and technical guidance to enhance user experience and self-service capabilities
Participate in evaluation and adoption of new technologies to advance performance, efficiency, and sustainability in research computing
Qualification
Required
PhD in a quantitative discipline
Five years of experience in HPC user support, software deployment, and performance optimization within an academic or research environment
Additional education may substitute for required experience and additional related experience may substitute for required education beyond a high school diploma/graduation equivalent, to the extent permitted by the JHU equivalency formula
Preferred
Eight + years of professional experience in high-performance computing, large-scale systems, or research software engineering
Deep proficiency in Linux systems administration, performance tuning, and automation tools (Ansible, Terraform, Jenkins, or similar)
Experience with cluster management, workload schedulers (e.g., Slurm), and distributed or parallel file systems (e.g., GPFS, Lustre, WekaFS, Ceph)
Strong background in programming or scripting (Python, Bash, C/C++, Go, or Rust)
Familiarity with containerization and orchestration technologies used in HPC (Singularity, Apptainer, Docker, Kubernetes)
Understanding of high-speed interconnects (InfiniBand, 100/400 Gb Ethernet) and storage/data access patterns for AI and analytics
Experience developing or maintaining CI/CD pipelines and module environments (Lmod/Spack) for research software
Knowledge of GPU computing (CUDA, ROCm), MPI/OpenMP, and AI/ML frameworks
Demonstrated ability to collaborate with researchers on performance optimization, workflow design, and reproducible computing
Company
Inside Higher Ed
Inside Higher Ed is the online source for news, opinion, and jobs related to higher education.
51-200 employees
Funding
Current Stage
Growth StageTotal Funding
unknown2022-01-10Acquired
2006-08-31Series Unknown
Leadership Team
Stephanie Shweiki
Director, Foundation Partnerships
Recent News
Research & Development World
2025-05-03
Business Standard India
2025-04-11
Company data provided by crunchbase