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High Performance Computing Engineer Jobs in Michigan

Kla

HPC / AI Software Infrastructure Lead (E)

Ann Arbor, MI · On-site

$151K - $256K/yr

... computing (CUDA, ROCm) and modern AI frameworks (PyTorch, TensorFlow, etc.) * Familiarity with high-performance storage systems, networking, and data pipelines * Strong foundation in CI/CD, DevOps, ...

Kla

Senior Instrumentation Software Engineer

Ann Arbor, MI · On-site

$105K - $180K/yr

These semi sophisticated products which include robotics, high performance and distributed computing, data analytics and machine control. Job Responsibilities : * As a Senior Engineer, drive the ...

Veeco

$67K - $86K/yr

... and high-performance computing to next-generation electronics. We're seeking a hands-on Manufacturing Engineer to help bring complex electromechanical systems from design to reality. In this role ...

Deloitte

HPC AI Solution Architect (S2S)

Detroit, MI · On-site

... Engineering practice, you will design and drive deployment of fully integrated architectures for GPU-accelerated AI factories and high-performance computing infrastructure in close partnership with ...

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High Performance Computing Engineer information

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How much do high performance computing engineer jobs pay per hour?

As of Sep 11, 2026, the average hourly pay for high performance computing engineer in Michigan is $52.39, according to ZipRecruiter salary data. Most workers in this role earn between $42.93 and $59.28 per hour, depending on experience, location, and employer.

What is a high performance computing engineer?

A High Performance Computing (HPC) Engineer is a specialist who designs, builds, and maintains advanced computing systems that deliver exceptional processing power for complex computational tasks. These professionals optimize hardware and software environments to support scientific research, large-scale simulations, and data-intensive applications. They work with supercomputers, clusters, and cloud HPC resources, ensuring high efficiency, scalability, and reliability. HPC Engineers also support researchers and organizations in maximizing the performance of their computing infrastructure.

What are the key skills and qualifications needed to thrive as a high performance computing engineer?

To thrive as a High Performance Computing (HPC) Engineer, you need a strong background in computer science, parallel programming, and distributed systems, typically supported by a relevant degree. Familiarity with HPC clusters, Linux/Unix environments, programming languages like C/C++ or Python, and tools such as MPI, OpenMP, and job schedulers is essential. Analytical thinking, problem-solving, and effective teamwork are crucial soft skills for optimizing system performance and collaborating with researchers or end-users. These abilities ensure efficient computational solutions, maximize resource utilization, and drive innovation in data-intensive scientific or engineering projects.

What are some common challenges high performance computing engineers face when optimizing system performance?

High Performance Computing Engineers often encounter challenges such as balancing resource allocation, managing workload distribution, and minimizing system bottlenecks. They must ensure that hardware and software components interact efficiently, which can require deep knowledge of parallel computing, networking, and storage systems. Additionally, staying up-to-date with rapidly evolving technologies and troubleshooting complex performance issues are integral parts of the role. Collaborating closely with researchers and IT teams is essential to tailor solutions that meet specific computational needs.

What is the difference between High Performance Computing Engineer vs Data Scientist?

AspectHigh Performance Computing EngineerData Scientist
Required CredentialsBachelor's or master's in computer science, engineering, or related fields; knowledge of parallel computingBachelor's or master's in data science, statistics, or related fields; programming skills in Python, R
Work EnvironmentResearch labs, tech companies, supercomputing centersBusiness, tech firms, research institutions
Industry UsageSupercomputing, scientific research, simulationsData analysis, machine learning, predictive modeling

High Performance Computing Engineers focus on developing and optimizing large-scale computing systems for scientific and technical applications, while Data Scientists analyze data to extract insights. Both roles require programming skills and work in tech-driven environments, but their core objectives differ: system performance versus data analysis.

What are popular job titles related to High Performance Computing Engineer jobs in Michigan?

For High Performance Computing Engineer jobs in Michigan, the most frequently searched job titles are:

What job categories do people searching High Performance Computing Engineer jobs in Michigan look for?

The top searched job categories for High Performance Computing Engineer jobs in Michigan are:

High Performance Computing Engineer jobs near you
Infographic showing various High Performance Computing Engineer job openings in Michigan as of September 2026, with employment types broken down into 1% As Needed, 78% Full Time, 16% Part Time, 3% Contract, and 2% Nights. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution, with an average salary of $108,966 per year, or $52.4 per hour.

CAE HPC System Administrator _Saline , MI

Saline, MI

iFlow Inc
See more jobs at iFlow Incexternal

Full-time

Posted 2 days ago

New

Job description

Job Title: CAE HPC System Administrator
Location: ENGINEERING DIVISION Saline, Michigan, United States
Duration:6 Months
Experience:10-15 Years

Description
We are seeking a highly skilled Computer Aided Engineering High Performance Computing (CAE HPC) System Administrator to manage, optimize, and support enterprise-level High-Performance Computing (HPC) environments dedicated to Computer-Aided Engineering (CAE) workloads.
This role is responsible for ensuring system stability, scalability, and performance of HPC clusters while supporting CAE applications, job scheduling systems, and underlying Linux infrastructure. The ideal candidate combines strong Linux systems expertise, HPC workload management experience, and a solid understanding of CAE engineering environments.

Key Responsibilities:
1. HPC Job Queuing & Workload Management
Administer, configure, and optimize HPC job scheduling environments, including IBM Spectrum LSF, Open PBS, or equivalent schedulers.
Design and tune job queues, resource allocation policies, and scheduling strategies to support diverse CAE workloads.
Monitor system performance and utilization trends and implement improvements to maximize efficiency and throughput.
2. CAE Application and Licensing Support
Install, upgrade, test, and support CAE applications and simulation tools in production environments.
Provide integration support between CAE applications and HPC scheduling systems.
Manage CAE software licensing systems (e.g., FlexLM, RLM) and ensure availability.
Troubleshoot application-related issues and ensure minimal disruption to engineering activities.
3. Linux Systems Administration & Automation
Administer and maintain Red Hat Enterprise Linux (RHEL) environments across HPC clusters.
Perform OS provisioning, deployment, and patch management using automated tools (e.g., PXE, or configuration management solutions).
Develop and maintain scripts (Bash, Korn shell, C Shell, Perl, Awk, or equivalent) to automate system monitoring, health checks, and routine administrative tasks.
o Maintain system logs, monitoring processes, and standard operating procedures.
1. Hardware & Infrastructure Management
Troubleshoot and resolve issues related to servers, storage systems, and high-performance networking (e.g., InfiniBand, high-speed Ethernet).
Support hardware lifecycle activities including installation, maintenance, and upgrades.
Conduct capacity planning based on system utilization trends and future demand.
2. Operations, Monitoring & Continuous Improvement
Perform system health checks, monitoring, and incident tracking for HPC and CAE environments.
Document system configurations, procedures, incidents, and best practices.
Track outages, analyze root causes, and implement preventive measures.
Follow change management processes for system updates and deployments.
Provide accurate reporting (e.g., utilization, incidents, system performance) and support project initiatives.

Requirements
3+ years of Linux system administration experience (preferably RHEL environments).
Hands-on experience managing HPC clusters and job schedulers (LSF, Slurm, PBS, or similar).
Proven experience in CAE application support and integration.
Strong scripting skills (Bash, Shell, Perl, or equivalent).
Experience with OS deployment, patching, and system automation.
Solid understanding of enterprise server hardware, storage, and networking fundamentals.
Experience with CAE tools such as Ansys, LS-DYNA, Nastran, or similar.
Familiarity with high-performance networking technologies is plus (e.g., InfiniBand).
Experience developing internal tools or dashboards are plus (e.g., PHP or web-based tooling).
Position Type / Expected Hours
Hybrid Full-time: Standard business hours with flexibility required to support maintenance windows and critical production issues.
Occasional after-hours or weekend work may be required based on business needs.