Senior Cyberinfrastructure Engineer for HPC and GPU Solutions

2 weeks ago


Wilmington, North Carolina, United States InsideHigherEd Full time

Position Title: Research Cyberinfrastructure Engineer II, HPC and GPU Cluster

Department: Research Cyberinfrastructure

Salary Range: $99,400 - $114,300

Role Overview: The Research Cyberinfrastructure Engineer II (RCIEII) plays a pivotal role in enhancing the computing infrastructure dedicated to research. This position emphasizes the administration of High-Performance Computing (HPC) environments, cloud services, and advanced computational solutions. A key responsibility includes the development and management of a graphical processing unit (GPU) cluster, primarily utilized for artificial intelligence (AI) and machine learning (ML) applications.

Key Responsibilities:

  • Project Leadership: Oversee and optimize HPC systems and cloud infrastructures, ensuring high performance and availability.
  • Innovation: Introduce state-of-the-art computing services and applications, integrating GPU technologies into existing HPC frameworks.
  • Collaboration: Forge strategic alliances with IT departments, technology vendors, and research teams to promote cooperative efforts.
  • Mentorship: Develop platforms for knowledge sharing, organize workshops and hackathons, and encourage ongoing professional development.

Qualifications:

  • Bachelor's degree in Computer Science, Information Technology, or a related field.
  • A minimum of 3 years of experience in research computing, with a focus on optimizing HPC systems and ensuring security.
  • Proficient in scripting languages (Python, Bash) and automation tools (Ansible, Terraform).
  • Strong expertise in managing Linux and Windows servers, as well as container technologies (Docker, Kubernetes).
  • Experience with cloud platforms (AWS, Azure, Google Cloud) and deploying HPC software.

Why Choose This Role?

  • Impactful Contributions: Engage in significant research and innovative projects that drive advancements.
  • Collaborative Culture: Work alongside a diverse team of professionals from various disciplines.
  • Opportunities for Growth: Access to continuous learning and professional development resources.

Preferred Qualifications:

  • Advanced degree or relevant certifications.
  • Expertise in AI/ML software and frameworks.
  • Experience with CUDA programming and/or C/C++.
  • Professional certifications such as AWS Certified Solutions Architect or Google Cloud Professional Cloud Architect.

Commitment to Diversity: The organization is an equal opportunity employer, dedicated to fostering diversity and inclusion. Applications from all underrepresented groups are highly encouraged.



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