Research Cyberinfrastructure Architect, UNLV Research [R0152139]

University of Nevada Las Vegas•Las Vegas, MD

18d•Onsite

About The Position

The research cyberinfrastructure architect has a strong technical background in research computing and a passion for empowering new users of advanced cyberinfrastructure (CI). UNLV is an emerging R1, EPSCoR institution with a growing investment in expanding cyberinfrastructure. The position is part of a collaboration between UNLV IT and the Division of Research to leverage all opportunities in delivering cutting edge technology and supportive cyberinfrastructure services. As part of a growing team focused on delivering a wider range of solutions through collaboration with enterprise IT staff, faculty, students and regional and national research data and computing community, the research computing architect is collaborator who enjoys a key role in delivering high-performance computing (HPC) eco-systems with user-friendly solutions for data intensive research and teaching. The architect partners with campus stakeholders to architect and implement IT infrastructure services that sustain current research and prepare to support research and teaching of emerging technologies. The position helps to develop and maintain systems, storage, networking and data architecture to support research, teaching, and workforce development. The role is designed for an individual who is looking to enjoy a more impactful role in building systems to accelerate research and transform data-intensive learning experiences. The position requires experience collaborating with IT teams in implementing research technologies that include high performance computing, research networks, cloud computing, and AI/ML technologies. Equally important is an inclusive and innovative outlook, towards lowering the barriers to gaining proficiency in advanced computing technologies and using advanced computing.

Requirements

Knowledge of a variety of HPC systems (CPU, GPU, storage systems, file systems, networking, virtualization, job schedulers (Slurm) and scientific applications)
Expert knowledge of database, filesystem, networking, server, operating system, and software concepts directly applicable to team science, internet-of-things, cloud architecture, cluster computing, and user management.
Familiarity with facilitation techniques used to engage researchers from a variety of disciplines
Experience in developing strategic plans and initiatives, gathering key performance and requirements, and achieving consensus among diverse and potentially competitive stakeholders.
Experience leading the implementation of technically complex projects affecting many end-users across multiple disciplines and functional areas.
Experience with Science and Research networks.
Experience in software infrastructure design, deployment, and management.
Subject Matter Expert (SME) level understanding of OS (especially UNIX/Linux) systems administration.
Experience managing high performance computing information technology systems and services through their full lifecycles in an academic or research agency environment.
Ability to work without direct supervision.
Ability to learn, deeply understand, and communicate the salient aspects of complex and novel research data system designs and architectures to peers in the University as well as scientific and engineering personnel.
Ability to effectively lead, supervise, manage, and/or delegate to other staff whose subject matter expertise and technical areas of focus may not closely align with the Research Architect’s own strengths and experience.
Ability to determine and effectively communicate strategic technology platform decisions in support of key research and science-based service missions and initiatives across the University and NSHE institutions.
Ability to manage multiple projects and meet deadlines.
Demonstrate professionalism and collegiality.
Bachelor’s degree from an accredited college or university as recognized by the United States Department of Education and/or the Council on Higher Education Accreditation (CHEA)
5+ years of experience
Experience working in a higher education or research-intensive setting
Demonstrated success in working with a research team supported federal and/or regional research grants
5+ years of experience in HPC architecture or a related field

Nice To Haves

Knowledge of containerization technologies (Kubernetes, Singularity, etc.)
Knowledge of managing GPUs, MPI, InfiniBand, XDMod
Knowledge of AI/ML Packages
Understanding of at least two or more additional technologies listed (data structures related to research, data management plans, data-facing scientific instruments, data workflows, data staging and transfer systems, identity and access management, software utilized in research and cloud technologies)
Experience in design/deployment of data workflows, especially for team science across distributed computing systems and networks.
Experience with successful technical grant writing for science or engineering research, technology R&D, and/or technology infrastructure.
Experience in contributing to national research and data community through workgroups, best practice papers, presentations or organizing and hosting technology sessions in scientific and engineering conferences.
Experience designing or implementing HPC workforce development programs
Be flexible and adaptable, which includes embracing new opportunities and unforeseen challenges.
Demonstrated success developing plans in the areas of research computing, data, and cyberinfrastructure within an academic setting
Experience with designing and implementing HPC systems and solutions.
Familiarity with parallel computing, distributed systems, and cloud integration.

Responsibilities

Lead the design and development of HPC solutions, ensuring alignment with the university’s strategic objectives and research needs.
Develop architectural blueprints and roadmaps for HPC systems, including hardware, software, and networking components.
Work closely with researchers and UNLV IT teams to understand computational requirements and translate them into scalable and efficient HPC solutions.
Evaluate emerging technologies and trends in HPC to inform strategic planning and decision-making.
Establish and enforce architectural standards and best practices to ensure consistency and quality across HPC solutions.
Create and maintain comprehensive documentation for HPC architectures and provide training and guidance to stakeholders.