Edtech.com's Summary

Penn State University is hiring a Research Computing Engineer for AI Infrastructure and HPC. This role at the Institute for Computational and Data Sciences designs, operates, and optimizes the GPU, AI, and high-performance computing infrastructure that Penn State researchers rely on for machine learning and computational science. The engineer works across compute, storage, networking, and automation to keep research workflows running reliably at University Park.

Highlights

Designs and operates GPU and HPC infrastructure supporting AI and research computing
Automates and optimizes systems using DevOps and infrastructure-as-code practices
Diagnoses issues across compute, storage, networking, and software environments
Partners with researchers to translate workload requirements into engineering solutions
Supports security, logging, documentation, and compliance for federally regulated systems
Evaluates tools and workflows for AI model training, inference, and large-scale data movement
Pays $81,312-$122,016 per year
Requires a bachelor’s degree and 1+ years of relevant experience
Requires U.S. citizenship due to access requirements
On-site role at University Park, PA; not eligible for remote work

Research Computing Engineer (AI Infrastructure and HPC) Full Description

Position Specifics

The Institute for Computational and Data Sciences (ICDS) at Penn State seeks a Research Computing Engineer to join its technical team. This role supports Penn State’s research mission by designing, operating, automating, and optimizing the GPU, AI, and computing infrastructure used by researchers across the university, along with the high-performance computing systems that support it. This position will be filled at the Research Computing Systems Engineer - Intermediate Professional level. Candidates must be U.S. citizens due to specific access requirements associated with this position.

This position is ideal for an engineer who enjoys building reliable, scalable systems for machine learning, data-intensive research, and advanced computing workloads. The successful candidate will work across GPU systems, HPC platforms, storage, networking, automation, and user-facing research workflows to enable cutting-edge research in AI, simulation, and computational science.

Work Arrangement: This is a full-time position, which will report to the Research HPC Manager and requires on-site work at University Park and is not supportive of remote work.

Responsibilities

Collaborate with teammates, users, and vendor support to diagnose issues and implement solutions across compute, storage, networking, and software environments
Monitor, maintain, automate, and improve AI and HPC systems and supporting infrastructure
Design, deploy, operate, troubleshoot, and optimize systems using DevOps and infrastructure-as-code practices
Support GPU-accelerated computing environments for AI, machine learning, and scientific workloads
Partner with researchers and ICDS staff to understand workload requirements and develop engineering solutions for system configuration, performance, and research workflows
Support security, logging, documentation, and compliance processes for the systems operated, including environments subject to federal research security
Contribute to planning, requirements gathering, process improvement, and operational readiness for new services and infrastructure
Provide timely updates to system documentation and respond to user questions with clear, actionable guidance
Evaluate and improve tools, platforms, and workflows that support AI model development, training, inference, and data movement at scale

Required Qualifications

Ability to work effectively in a Linux environment, including command-line tools, file editing, POSIX permissions, and system configuration
Strong scripting ability in Bash and Python
Strong problem-solving skills and the ability to debug complex systems
Ability to work collaboratively as part of a technical team
Experience using AI tools or AI agents to improve programming, debugging, development, or prototyping workflows
Clear written and verbal communication skills

Preferred Qualifications

Experience with any of the following is helpful but not required:

Administration of multi-GPU nodes at scale, including driver/firmware lifecycle management, NVLink/NVSwitch topology validation, and GPU health monitoring
Experience supporting AI/ML infrastructure for model training, inference, experiment workflows, and large-scale data processing
Experience with job schedulers such as Slurm, PBS, HTCondor, or LSF
Software development experience with HPC programming environments such as C/C++, Fortran, CUDA, MPI, or OpenMP
DevOps experience, including Git-based workflows, CI/CD, automation, and collaborative development practices
Experience with deployment tools such as xCAT, Warewulf, OpenCHAMI, OpenStack/Bifrost, or MAAS
Experience administering or supporting Kubernetes
Experience with virtualization/containerization technologies such as VMware, Docker, Apptainer, or Podman
Networking experience including EVPN, BGP, and IPv6
Experience with high-speed interconnects such as InfiniBand or HPE Slingshot
Experience with HPC or distributed storage systems such as GPFS, Lustre, Ceph, or VAST
Monitoring and observability experience with tools such as Grafana, Graphite, Prometheus, VictoriaMetrics, or InfluxDB
Experience with databases such as MySQL/MariaDB or PostgreSQL
Security experience including identity and access management, single sign-on, and LDAP/Active Directory
Familiarity with Agile project development
Prior experience in academic research computing, research data infrastructure, or large-scale shared computing environments

Application Instructions

To receive full consideration for the position, applications should include a cover letter expressing the candidate’s interest in the role and a current curriculum vitae (CV) or resume.

Minimum Education, Work Experience & Certifications

Bachelor’s Degree and 1+ years of relevant experience; or an equivalent combination of education and experience accepted. No certifications required.

Background Checks/Clearances

Employment with the University will require successful completion of background check(s) in accordance with University policies. Penn State does not sponsor or take over sponsorship of a staff employment Visa; applicants must be authorized to work in the U.S.

Salary & Benefits

The salary range for this position, including all possible grades, is $81,312.00 - $122,016.00. Penn State provides a competitive benefits package for full-time employees, including comprehensive medical, dental, and vision coverage, robust retirement plans, substantial paid time off, and a generous 75% tuition discount available to employees as well as eligible spouses and children.

EEO Is the Law

Penn State is an equal opportunity employer and is committed to providing employment opportunities to all qualified applicants without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.

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Research Computing Engineer (AI Infrastructure and HPC)

Edtech.com's Summary

Research Computing Engineer (AI Infrastructure and HPC) Full Description

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