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Gpu Computing Jobs in Missouri (NOW HIRING)

Jobgether

Exposure to cutting-edge technologies across distributed systems, GPU computing, and large-scale AI model serving. * High level of ownership and influence over technical decisions and engineering ...

Introl

Data Center Technician

Kansas City, MO · On-site

$30 - $36/hr

The region is growing as a hub for cloud computing and GPU infrastructure deployments. About Introl Introl stands apart as a leader in GPU infrastructure deployments, specializing in large-scale GPU ...

Accenture

AI & HPC Infrastructure Engineer

Saint Louis, MO · On-site

$97K - $127K/yr

... GPU-accelerated workloads, large-scale models, simulations, and emerging agentic AI solutions at ... Design and implement AI infrastructure and accelerated computing solutions, aligning system ...

Nebius

Data Center IT Manager

Kansas City, MO

$146K - $220K/yr

... computing (HPC), and hyperscale cloud services . Our data centers host large-scale GPU clusters purpose-built for AI training, inference, and accelerated workloads. As global data center operations ...

Nebius

Data Center IT Manager

Kansas City, MO · On-site

$146K - $220K/yr

... computing (HPC), and hyperscale cloud services . Our data centers host large-scale GPU clusters purpose-built for AI training, inference, and accelerated workloads. As global data center operations ...

Jobgether

... scale computing environments. * Proficiency with PyTorch and modern machine learning development workflows. * Ability to work close to hardware constraints, including GPU performance, memory ...

Nebius

Regional Asset Manager

Kansas City, MO

Why work at Nebius Nebius is leading a new era in cloud computing to serve the global AI economy ... scale GPU clusters and AI infrastructure deployed across multiple regions. Our teams are ...

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Gpu Computing information

What is GPU computing?

GPU computing refers to the use of a Graphics Processing Unit (GPU) alongside a Central Processing Unit (CPU) to accelerate computational tasks. GPUs are highly efficient at performing parallel operations, making them ideal for complex calculations in fields like machine learning, scientific simulations, and graphics rendering. Unlike traditional CPUs, GPUs can process thousands of threads simultaneously, greatly speeding up tasks that involve large-scale data processing. This makes GPU computing essential in industries requiring high-performance computing solutions.

What are some common challenges faced by GPU Computing professionals when optimizing code for parallel processing?

One of the main challenges in GPU Computing is efficiently restructuring code to leverage the massive parallelism that GPUs offer. Professionals often encounter issues with memory management, synchronization between threads, and minimizing data transfer between CPU and GPU to avoid bottlenecks. Additionally, debugging parallel code can be complex, as errors may not manifest consistently across runs. Collaborating with software engineers, data scientists, and hardware specialists is typical to ensure optimal performance and scalability in real-world applications.

What is the difference between Gpu Computing vs Data Scientist?

AspectGpu ComputingData Scientist
Required CredentialsKnowledge of GPU architectures, programming skills in CUDA or OpenCLDegree in Computer Science, Statistics, or related fields; strong programming skills
Work EnvironmentHigh-performance computing environments, data centers, research labsOffice settings, research institutions, tech companies
Industry UsageMachine learning, scientific simulations, graphics renderingData analysis, predictive modeling, business insights

Gpu Computing focuses on leveraging GPU hardware for high-speed processing tasks, often requiring specialized programming skills. Data Scientists analyze data to extract insights, using various tools and statistical methods. While both roles involve data and computing, Gpu Computing is more hardware and performance-oriented, whereas Data Scientists focus on data analysis and modeling.

What are the key skills and qualifications needed to thrive as a GPU Computing Specialist, and why are they important?

To thrive as a GPU Computing Specialist, you need expertise in parallel programming, computer architecture, and a strong foundation in mathematics and algorithms, often supported by a degree in computer science, engineering, or related fields. Familiarity with programming languages like C/C++, CUDA, OpenCL, and experience with GPU hardware and high-performance computing systems are essential. Problem-solving abilities, analytical thinking, and strong collaboration skills help you innovate and work effectively on complex computational projects. These skills ensure efficient development, optimization, and deployment of GPU-accelerated solutions crucial for scientific, engineering, and AI applications.
What are popular job titles related to Gpu Computing jobs in Missouri? For Gpu Computing jobs in Missouri, the most frequently searched job titles are:
What job categories do people searching Gpu Computing jobs in Missouri look for? The top searched job categories for Gpu Computing jobs in Missouri are:
Gpu Computing jobs near you
Infographic showing various Gpu Computing job openings in Missouri as of July 2026, with employment types broken down into 86% Full Time, 12% Part Time, and 2% Contract. Highlights an 79% Physical, 3% Hybrid, and 18% Remote job distribution.
High Performance Computing (HPC) Engineer

High Performance Computing (HPC) Engineer

Federal Reserve Bank of Richmond

Kansas City, MO

Full-time

Posted 17 days ago

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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