Machine Learning Research Computing Facilitator

The Center for High Throughput Computing (CHTC) is hiring a Machine Learning Research Computing Facilitator to join the Research Computing Facilitation team. CHTC's Research Computing Facilitation team introduces researchers to large-scale computational approaches and enables their use of large-scale computing systems like CHTC's in-house clusters and the Open Science Pool and PATh Facility (operated by the NSF Partnership to Advance Throughput Computing (PATh) project). The Machine Learning Facilitator role complements the existing Facilitation team by providing specific support to researchers regarding AI/machine learning (ML) methods and implementation on shared computing systems.

Specific tasks for this role may include:

• Formalize an understanding of automation, data and computing needs for AI workloads and communicate these with the CHTC team.

• Provide recommendations and develop reference examples, prompts, & scripts for specific needs for AI/ML workloads. Example Techniques include:

  • Implementing checkpointing

  • Handling large datasets

  • Managing large number of tasks (for inference)

  • Profiling GPU code

• Develop and deliver presentations, training materials and user guides specific to AI workloads.

• Participate in campus events around AI and connect AI users with shared problems and solutions at CHTC.

• Identify gaps in tooling and recommendations for CHTC users to leverage agentic AI.

• Provide input into and manage owned capacity and priority schemes.

The preferred applicant has experience in applying AI/ML methods to research questions. They are motivated to help other researchers deploy machine learning methods in a cluster computing environment and to understand what challenges these researchers face in scaling their machine learning workloads. They are able to communicate about technical concepts to a general audience and successfully collaborate with their teammates and other teams in the organization. They are interested in pursuing broad knowledge of the field and are able to learn unfamiliar technologies. New team members will be supported in learning about high-throughput technologies and supporting High-Throughput Computing workloads.

This position reports to the Research Computing Facilitation Lead at CHTC. This position is 100% onsite, with work space in Morgridge Hall.

• Contributes to the design and content development of documentation, training content, and/or advanced curricula, and instructs at workshops

• May provide consultation and expertise for aspects of research proposals specific to research CI. May serve as a project contributor for a research proposal or Co-Principal Investigator on proposals around facilitation functions

• Connects and coordinates interactions between researchers and technology providers. Provides regular communications to and/or collaborates with the systems and software/data professionals regarding service enhancements

• Communicates and collaborates with internal collaborators and/or potential external collaborators around facilitation and relevant service models

• Engages with researchers in their selection and use of relevant CI systems, tools, and computing strategies. Contributes to facilitating the design and debugging of research workflows alongside researchers

• May contribute to regular communications with researchers and internal stakeholders

College of Computing and AI, Computer Sciences, Center for High Throughput Computing.

CHTC is a research center at UW - Madison and home to campus computing services. Housed across the Computer Science Department and Morgridge Institute for Research, we are practitioners of translational computer science. CHTC develops technologies to advance high throughput computing and then deploys those technologies and provides computing capacity to a broad community of researchers, with the goal of continuously responding to researcher feedback and enabling them to advance their work. Our leadership in the Partnership to Advance Throughput Computing (PATh) Project represents this commitment to developing tools and communities around these tools.

The minimum salary for this position is $71 994. This position offers a comprehensive benefits package, including generous paid time off, competitively priced health/dental/vision/life insurance, tax-advantaged savings accounts, and participation in the nationally recognized Wisconsin Retirement System (WRS) pension fund. For a summary of benefits, please see https://www.wisconsin.edu/ohrwd/benefits/download/fasl.pdf.

• At least a year of work or study experience in an industry or academic research group.

• Experience working with common machine learning tools (e.g. python, pytorch) to solve research questions.

• Demonstrated interest and experience in teaching or mentoring peers.

• Experience using agentic AI as part of daily workflows.

• Experience working with datasets greater than 300GB in size.

• Experience with different dataset file formats

• Experience using cluster or distributed computing systems, like Kubernetes, SLURM, HTCondor, etc.

• Experience in a user support or education role.

Bachelor's Degree Required

Click the "Apply" button to start the application process.

To be considered for this recruitment, you must upload:

-Resume

-Cover Letter

In materials, please address your experience with the job qualifications and duties listed in the posting.

There is only one attachment field; please upload all application materials here. All listed application materials must be submitted for your application to be considered. Please submit only the materials specified; additional materials will not be reviewed.

Please note that successful applicants are responsible for ensuring their eligibility to work in the United States (i.e. a citizen or national of the United States, a lawful permanent resident, a foreign national authorized to work in the United States without need of employer sponsorship) on or before the effective date of appointment.

Becky Bush

hiring@cs.wisc.edu

Relay Access (WTRS): 7-1-1. SeeRELAY_SERVICEfor further information.

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