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Hpc Performance Engineer Jobs in Chicago, IL (NOW HIRING)

Chupdown

System Software Engineer

Chicago, IL · On-site

$150 - $200/hr

With 1000x performance of today's cloud-based approaches, UpDown enables instant real-time mapping ... We are looking for a talented System Software engineer, experienced with Linux and HPC, and capable ...

Clean Harbors

Sales Engineer, Data Centers

Chicago, IL · On-site +1

$133K/yr

HPC-Industrial, powered by Clean Harbors, is looking for a Data Center Sales Engineer to join their ... We are committed to safety, people, growth, service, and performance. We provide the safest, most ...

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Hpc Performance Engineer information

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How much do hpc performance engineer jobs pay per hour?

As of Sep 11, 2026, the average hourly pay for hpc performance engineer in Chicago, IL is $61.92, according to ZipRecruiter salary data. Most workers in this role earn between $50.77 and $70.10 per hour, depending on experience, location, and employer.

What is an HPC performance engineer?

HPC Performance Engineers are specialists who focus on optimizing the performance of high-performance computing (HPC) systems and applications. They analyze system bottlenecks, tune software and hardware configurations, and work with researchers and developers to ensure applications run efficiently on supercomputers or large computing clusters. Their work is essential for maximizing computational resources and improving the speed and scalability of scientific, engineering, or data-intensive workloads.

What are the key skills and qualifications needed to thrive as an HPC performance engineer?

To thrive as an HPC Performance Engineer, you need a strong background in computer science or engineering, with expertise in parallel programming, high-performance computing architectures, and performance analysis. Familiarity with tools like MPI, OpenMP, profiling software (e.g., Intel VTune, GNU gprof), and experience with job schedulers and Linux systems are essential. Analytical thinking, problem-solving, and effective communication are crucial soft skills for identifying bottlenecks and collaborating with multidisciplinary teams. These skills are vital for optimizing computational workflows, maximizing resource utilization, and driving efficiency in complex HPC environments.

What are the typical challenges HPC performance engineers face when optimizing large-scale computational workloads?

HPC Performance Engineers often encounter challenges such as identifying bottlenecks in parallel code, managing resource contention, and optimizing data movement across distributed systems. They must balance maximizing throughput with minimizing latency, all while ensuring applications scale efficiently as cluster sizes grow. Collaboration with software developers, system administrators, and research teams is common to align application requirements with hardware capabilities and to implement effective performance improvements.

What is the difference between Hpc Performance Engineer vs Hpc System Administrator?

AspectHpc Performance EngineerHpc System Administrator
Primary FocusOptimizing HPC system performance and efficiencyManaging and maintaining HPC infrastructure
Skills & CertificationsPerformance tuning, parallel computing, Linux, scriptingSystem setup, network management, user support
Work EnvironmentResearch labs, data centers, high-performance computing facilitiesData centers, IT departments, research institutions
Common TasksPerformance analysis, bottleneck resolution, code optimizationSystem installation, user account management, hardware troubleshooting

The Hpc Performance Engineer focuses on enhancing system performance and efficiency, often working on optimization and tuning. In contrast, the Hpc System Administrator manages the day-to-day operation and maintenance of HPC systems. Both roles are essential in high-performance computing environments but serve different core functions.

Hpc Performance Engineer jobs near you

System Software Engineer

Chicago, IL • On-site

Chupdown
See more jobs at Chupdownexternal

$150 - $200/hr

Other

This job post has expired 3 days ago. Applications are no longer accepted.

Job description

At Chicago UpDown, we are building breakthrough graph computing acceleration - software and hardware. With 1000x performance of today's cloud-based approaches, UpDown enables instant real-time mapping and analytics of trillion-node graphs. The core technologies were created as part of IARPA's AGILE program, and spun out from the University of Chicago and Purdue University.

We are looking for a talented System Software engineer, experienced with Linux and HPC, and capable with advanced AI tools to lead the design and enhancement of system software for a sophisticated, scalable global memory management and scale-out parallel cluster system (>10,000 nodes).

We are seeking a talented System Software Engineer to design, build, and optimize the memory and system software stack for our scalable, accelerator-based global memory system, UpDown.

Challenges include accelerator global memory (petabytes of unified virtual memory) and resource management in large-scale parallel systems (cloud and HPC-like). The technical challenges exceed the largest cloud and HPC systems today.

Key Responsibilities

Lead the design and implementation of a petabyte-scale unified virtual memory system to leverage novel hardware translation features and capabilities.

Global Memory and system library: System and application allocators & runtimes, including custom memory allocators and system-level runtime infrastructure to maximize throughput.

Task/Job Scheduling & Orchestration: Integrate and optimize HPC workload managers and job scheduling systems (such as Slurm, PBS, or custom schedulers) to efficiently allocate resources and orchestrate massively parallel jobs.

Kernel and Driver Engineering: Linux kernel and driver work to support and optimize the memory management and device driver subsystem, develop custom modules, and eliminate kernel-space bottlenecks.

Minimum Qualifications

Education: Master’s or Ph.D. in CS, CE, or related field.

Systems Programming Experience: 3+ years of hands-on experience writing production-grade, low-level code in C and C++ and/or Linux kernel programming.

Virtual and Memory Management Knowledge: Deep understanding of OS-level memory management, virtual memory, paging, and custom memory allocators.

Parallel Computing or HPC Experience: 3+ years in HPC/Cloud scalable systems software, writing/modifying software for HPC, supercomputer, and accelerator environments.

Preferred Qualifications

5+ years hands-on experience developing or modifying OS kernels (Linux), hypervisors, or low-level runtime libraries.

Strong understanding of the challenges associated with memory management in multi-tenant, globally distributed cloud infrastructure.

Advanced Interconnects: Demonstrated experience working with high-performance network and memory fabrics, such as RDMA (RoCE, InfiniBand), CXL, and NVLink.

Experience with graph workloads and algorithms ("e.g., Graph500 BFS") on modern hardware.

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