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$153.5K

How much do high performance computing ai jobs pay per year?

As of Sep 9, 2026, the average yearly pay for high performance computing ai in the United States is $99,528.00, according to ZipRecruiter salary data. Most workers in this role earn between $65,500.00 and $126,000.00 per year, depending on experience, location, and employer.

What is high performance computing in AI?

High Performance Computing (HPC) in AI refers to the use of powerful computers and clusters to process and analyze large volumes of data at high speeds, enabling complex artificial intelligence and machine learning tasks. HPC systems provide the computational power required to train deep learning models, run large-scale simulations, and handle big data analytics that are beyond the capability of standard computers. This technology is essential for accelerating AI research and applications in fields like healthcare, finance, and scientific research.

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

To thrive as a High Performance Computing AI specialist, you need expertise in parallel computing, deep learning frameworks, and a strong background in computer science or related fields, often with an advanced degree. Familiarity with tools such as CUDA, MPI, distributed computing systems, and certifications like NVIDIA Deep Learning Institute credentials are highly valued. Strong analytical thinking, collaboration, and problem-solving abilities set top professionals apart in this field. These skills are essential to optimize AI workloads, innovate scalable solutions, and ensure efficient resource utilization in complex computing environments.

What are common challenges high performance computing AI professionals face when optimizing AI workloads on supercomputers?

One of the main challenges for HPC AI professionals is efficiently scaling AI workloads across thousands of computing nodes while minimizing bottlenecks in data movement and network communication. Balancing the needs of deep learning models with the architecture of HPC systems often requires customizing software libraries and optimizing parallelization strategies. Additionally, integrating AI workflows with traditional simulation or modeling workloads can be complex, requiring strong collaboration with domain scientists and IT teams. Staying current with rapidly evolving hardware and software tools is also essential for success in this role.

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

AspectHigh Performance Computing AiData Scientist
Required CredentialsBachelor's or higher in Computer Science, Data Science, or related fields; experience with AI and HPC toolsBachelor's or higher in Statistics, Computer Science, or related fields; proficiency in data analysis and programming
Work EnvironmentResearch labs, tech companies, supercomputing centers focusing on AI workloadsBusiness, finance, healthcare, or tech sectors analyzing large datasets
Employer & Industry UsageOrganizations developing AI models using high-performance computing resourcesOrganizations extracting insights from data to inform decisions

High Performance Computing AI specialists focus on developing and optimizing AI models utilizing supercomputing resources, while Data Scientists analyze data to generate insights. Both roles require strong technical skills, but HPC AI emphasizes parallel computing and AI infrastructure, whereas Data Scientists focus on statistical analysis and data visualization.

What are popular job titles related to High Performance Computing Ai jobs?

For High Performance Computing Ai jobs, the most frequently searched job titles are:

Infographic showing various High Performance Computing Ai job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 16% Part Time, and 3% Contract. Highlights an 90% Physical, 1% Hybrid, and 9% Remote job distribution, with an average salary of $99,528 per year, or $47.9 per hour.

High Performance Computing (HPC) Engineer

Omaha, NE • On-site

Federal Reserve Bank of San Francisco
Public Administration • 1 - 5K employees
Learn more about Federal Reserve Bank of San Franciscoexternal

Full-time

Re-posted 2 days ago

Key responsibilities

  • Design, deploy, configure, and administer medium scale HPC clusters and associated storage systems.

  • Monitor system health, performance metrics, and resource utilization to ensure optimal operation.

  • Troubleshoot complex hardware and software issues in a multi-user research environment.

Job description

CompanyFederal Reserve Bank of Kansas CityWhen you join the Federal Reserve-the nation's central bank-you'll play a key role, collaborating with leading tech professionals to strengthen and protect our economic, financial and payments systems. We invest in contemporary and emerging technology each year to support the Federal Reserve and our economy, and we're building a dynamic and diverse team for our future.

Important Information

  • Open to US Citizens, Green Card holders or Permanent Residents with at least 3 years of residency, with the intent to become a US citizen.

  • No sponsorship is available. Candidates must have valid work authorization, without an end date, to be considered.

  • This position requires working on-site, in Kansas City, Denver, Oklahoma City or Omaha, with 5 days per month work from home flexibility. Relocation assistance is available.

About the Role

The Center for the Advancement of Data and Research in Economics (CADRE) supports data and computationally intensive research and analytics for staff in the Economic Research division of the Federal Reserve Bank of Kansas City and across the Federal Reserve System. Our services include multiple high performance computing environments, research data warehousing, and advanced analytical tools. We are an embedded technology team within the division of Economic Research, Regional, and Community Affairs.

We are seeking an experienced High Performance Computing Engineer who can plan, implement, and maintain advanced cyberinfrastructure solutions. The ideal candidate will have deep expertise in HPC architectures, parallel computing frameworks, and scientific computing applications. You will work independently while collaborating with researchers to solve complex computational challenges that support critical economic research initiatives.

Key Activities

Operations

  • Design, deploy, configure, and administer medium scale HPC clusters and associated storage systems.

  • Monitor system health, performance metrics, and resource utilization to ensure optimal operation.

  • Implement robust security protocols and perform regular maintenance including upgrades and patching.

  • Troubleshoot complex hardware and software issues in a multi-user research environment.

  • Manage job scheduling and workload optimization using tools like SLURM.

  • Administer parallel file systems (such as ceph and IBM Spectrum Scale/GPFS) and storage solutions.

Development

  • Design and implement innovative HPC solutions to address evolving research requirements.

  • Create and maintain automation scripts and tools to streamline system administration.

  • Optimize scientific applications and computational workflows for performance.

  • Implement container technologies (Docker, Singularity) for reproducible research.

  • Support GPU computing and accelerator technologies for specialized workloads.

  • Define and track performance metrics to ensure efficient current and future use of resources.

Partnership/Collaboration

  • Partner closely with researchers to understand computational needs and translate them into technical solutions.

  • Collaborate with network, security, and data center teams to ensure integrated operations.

  • Build and maintain relationships with external vendors and technology partners.

  • Participate in the HPC community to stay current with emerging technologies and best practices.

  • Serve as a technical advisor on infrastructure planning and technology roadmaps.

Documentation/Training

  • Develop comprehensive documentation for systems, policies, and procedures.

  • Create user guides and training materials for researchers utilizing HPC resources.

  • Provide mentorship to junior staff and knowledge sharing across teams.

  • Conduct workshops and training sessions on effective use of HPC resources.

Qualifications

Required

  • Bachelor's degree in computer science, engineering, mathematics, or related field, or equivalent combination of education and experience.

  • Minimum of 6 years of relevant experience in HPC administration and systems engineering.

  • Extensive experience with Linux operating systems (Red Hat/CentOS) in an HPC environment.

  • Strong command line skills and proficiency in scripting languages (Python, Bash).

  • Experience with job scheduling systems (SLURM, PBS, LSF) and resource management.

  • Knowledge of parallel file systems and storage technologies (e.g. ceph, GPFS, Lustre, BeeGFS).

  • Familiarity with parallel programming models (MPI, OpenMP) and scientific computing frameworks.

  • Experience with configuration management and automation tools (Salt, Ansible, Puppet).

  • Demonstrated problem-solving abilities and analytical thinking.

Preferred

  • Advanced degree in a computational field.

  • Experience with cloud computing platforms and hybrid HPC environments.

  • Experience with GitLab CI/CD pipelines for research software development.

  • Understanding of GPU computing and accelerator technologies (CUDA, OpenACC).

  • Experience supporting machine learning and AI workloads on HPC systems.

Additional Information

How We Work (HWW)

  • On-site: 5 days per month remote work flexibility

  • Location: Kansas City, Denver, Oklahoma City, or Omaha

  • Remote Eligible: No

  • Relocation Assistance: Yes

Salary

  • $110,300 - $155,700 / Senior Level

  • $125,200 - $176,700 / Advanced Level

  • $139,500 - $196,800 / Expert-Lead Level

  • Final offers are determined by factors including the candidate's qualifications, internal alignment considerations, district assignment, and geographic location.

Screening: US Citizens and Green Card holders or Permanent Residents with at least 3 years of residency, with the intent to become a US citizen. This position has additional screening requirements due to the information accessed while performing the job. These additional screenings would be initiated at the time of offer acceptance and could take up to a couple of months to be completed. You can begin work before the screening is completed; however, continued employment is contingent on acceptable screening results. The areas screened may include education/employment verification, criminal history, credit history, and reference checks.

Sponsorship: The Federal Reserve Bank of Kansas City will not sponsor a new applicant for employment authorization for this position. Applicants must be currently authorized to work in the United States without the need for visa sponsorship now or in the future.

About Us

  • Total Rewards & Benefits

  • Who We Are

  • What We Do

Follow us on LinkedIn, Instagram, X (formerly Twitter), and YouTube #KCFedIT

Full Time / Part TimeFull timeRegular / TemporaryRegularJob Exempt (Yes / No)YesJob CategoryInformation Technology Family GroupWork ShiftFirst (United States of America)

The Federal Reserve Banks are committed to equal employment opportunity for employees and job applicants in compliance with applicable law and to an environment where employees are valued for their differences.

Always verify and apply to jobs on Federal Reserve System Careers (https://rb.wd5.myworkdayjobs.com/FRS) or through verified Federal Reserve Bank social media channels.

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