HPC Sr. Scientific Software Engineer; IT@JH Research Computing

Specific Duties & Responsibilities

• Software Deployment and Design
  • 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).
• Performance Optimization
  • 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.
• Integration and Optimization
  • 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, Tensor
    
    RT, and Intel Compilers to enhance system performance.
• HPC Scientific Software Support
  • 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, Easy Build, Spack, and Lua module files.
• Collaboration and Mentorship
  • 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.
• Technical Support and Training Workshops and Troubleshooting
  • 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.
• Learning and Development
  • Stay current with advances in HPC and AI technologies and methodologies.
  • Incorporate new research findings into existing systems to improve performance and capabilities.
• Container Orchestration
  • 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.
• Documentation and Compliance
  • Create comprehensive documentation for system designs, performance metrics, and project status.
  • Ensure compliance with security and regulatory standards for all HPC and AI systems.
• In Addition to the Duties Described Above
  • 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.

• 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…