NYU's Stern School of Business has an exciting opportunity for a Research Computing Systems Manager within the Stern Center for Research Computing (SCRC). The Research Computing Systems Manager will manage cutting-edge research computing systems for the SCRC. Provide top-tier computational tools and services, supporting researchers in their groundbreaking work for publication in leading journals. Oversee daily operations and maintain the integrity and security of SCRC server systems across Linux/Windows platforms. Lead and manage server installation, monitoring, troubleshooting, and updates. Stay abreast of emerging trends in the field to keep SCRC’s technology leading-edge. Collaborate closely with researchers across Stern to understand and meet their computational needs and guide them in using commercial cloud services with GPU resources. Manage hardware configurations, performance tuning, and metrics. Research hardware solutions and advise on purchases.
The successful candidate will have a Bachelor's Degree in Computer Science, Information Systems, or a related field (a Master’s Degree in Computer Science is preferred) and 5+ years relevant experience, including experience installing, configuring, and maintaining server hardware/software in a complex networked environment and experience managing Linux (CentOS/Red Hat Enterprise Linux and Ubuntu) servers, or an equivalent combination of education and experience. Familiarity with Linux system administration and in-depth knowledge of Linux (RHEL/CentOS 7 and above, Ubuntu 20.04 and above) and shell scripting (Bash & Python) is required. Strong analytical, interpersonal, communication, teamwork, problem-solving, and customer service skills, along with the ability to work independently, take initiative, and learn and adopt new technologies are also required.
Experience with network-attached storage systems (preferably NetApp), Windows Server 2012 or higher, and VMWare ESXi/vCenter management, familiarity with public cloud infrastructure (Amazon Web Services, Google Cloud Platform, Azure) and containers (Docker, Kubnernetes, Singularity), familiarity with graphics processor unit (GPU) usage Cluster Computing and basic knowledge of Deep Learning is preferred. A working knowledge of relevant laws and regulations governing research computing systems and data, as well as familiarity with job scheduler/workload management (e.g., Slurm) is also preferred.
In compliance with NYC's Pay Transparency Act, the annual base salary range for this position is USD $90,000.00 to USD $110,000.00. New York University considers factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience, education/training, key skills, internal peer equity, as well as, market and organizational considerations when extending an offer. This pay range represents base pay only and excludes any additional items such as incentives, bonuses, clinical compensation, or other items.
New York University Stern School of Business is a welcoming community that inspires its employees to embrace and lead change in a rapidly transforming world. We offer a collegial and inclusive culture, and an excellent benefits package, which includes up to 100% NYU tuition waiver, generous vacation and holiday time off, health benefits, and flexible work policies. NYU and Stern provide access to a wide range of professional development resources, along with opportunities to build your career and expand your network. Located in the heart of Greenwich Village and deeply connected with the City for which it is named, NYU Stern is one of the nation’s premier management education schools and research centers. NYU Stern is a community that fosters inclusion, belonging, diversity and equity, and inspires its members to embrace change in a globally changing world. For more information about working at NYU please visit our website at: http://www.nyu.edu/about/careers-at-nyu.html.
NYU aims to be among the greenest urban campuses in the country and carbon neutral by 2040. Learn more at nyu.edu/nyugreen.
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