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Gpu Performance Engineer Jobs in Missouri (NOW HIRING)

Build GPU-enabled infrastructure * Deploy Longhorn storage * Automate infrastructure using ... Longhorn storage management and performance tuning * Canonical ecosystem tools (MAAS, Juju, Charmed ...

... Cloud GPU Services, with a strong focus on high-quality code, performance tuning, and cross ... CLI Development * Python Programming * Continuous Integration * RESTful Web Services ATS ...

From large-scale GPU orchestration to inference optimization, we own the hard problems across ... We offer competitive salaries, ranging from $125k- $180k base + quarterly performance bonuses. Join ...

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Gpu Performance Engineer information

What is a GPU performance engineer?

A GPU Performance Engineer is a specialist who analyzes, optimizes, and improves the performance of graphics processing units (GPUs). They work on identifying bottlenecks, optimizing code, and ensuring that GPU hardware and software deliver maximum efficiency and speed. Their role may involve working with drivers, firmware, and applications to enhance graphics and compute workloads. This job is essential in industries like gaming, AI, and high-performance computing where GPU efficiency directly impacts user experience and system performance.

What are some common challenges faced by a GPU performance engineer when optimizing graphics workloads?

GPU Performance Engineers often encounter challenges such as identifying performance bottlenecks within complex graphics pipelines, balancing resource utilization, and achieving optimal frame rates across diverse hardware configurations. They must use specialized profiling tools and collaborate closely with developers, driver engineers, and QA teams to address issues like memory bandwidth limitations or shader inefficiencies. Staying updated with rapidly evolving GPU architectures and optimizing for both current and next-generation hardware are also key aspects of the role.

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

To thrive as a GPU Performance Engineer, you need a strong background in computer architecture, programming (C/C++), and a degree in computer science, electrical engineering, or a related field. Proficiency with GPU profiling tools (e.g., NVIDIA Nsight, AMD Radeon GPU Profiler), performance analysis frameworks, and parallel computing libraries like CUDA or OpenCL is typically required. Analytical thinking, problem-solving abilities, and effective communication are crucial soft skills for collaborating with developers and debugging performance bottlenecks. These skills and qualities are essential for optimizing GPU performance, ensuring efficient software-hardware interaction, and delivering high-quality graphics or compute solutions.

What is the difference between Gpu Performance Engineer vs Gpu Hardware Engineer?

AspectGpu Performance EngineerGpu Hardware Engineer
Primary FocusOptimizing GPU performance, benchmarking, and tuning softwareDesigning, developing, and testing GPU hardware components
Required SkillsProgramming, performance analysis, GPU architecture knowledgeHardware design, circuit analysis, FPGA/ASIC experience
Work EnvironmentSoftware development teams, labs for testing performanceHardware labs, manufacturing facilities, R&D centers
Common CertificationsNone specific, often requires computer engineering or related degreesElectrical engineering, VLSI design certifications

The Gpu Performance Engineer primarily focuses on optimizing and testing GPU software performance, while the Gpu Hardware Engineer designs and develops the physical GPU components. Both roles require a strong background in computer engineering, but differ in their core responsibilities and work environments.

What are popular job titles related to Gpu Performance Engineer jobs in Missouri?

For Gpu Performance Engineer jobs in Missouri, the most frequently searched job titles are:

What job categories do people searching Gpu Performance Engineer jobs in Missouri look for?

The top searched job categories for Gpu Performance Engineer jobs in Missouri are:

What cities in Missouri are hiring for Gpu Performance Engineer jobs?

Cities in Missouri with the most Gpu Performance Engineer job openings:

Platform Engineer

Virtual Networx

Saint Louis, MO • On-site

Other

Posted 11 days ago


Job description

Role: Platform Engineer

Duration: 1 month

Location: St. Louis, MO

Role Overview
Highly skilled AI Infrastructure Engineer to design, build, and operate scalable GPU-enabled Kubernetes platforms for AI/ML workloads.

Must have skills: Kubernetes, Linux, Terraform, GPUs and NVIDIA stack

Required Qualifications

  • 3 8+ years' experience
  • Strong Kubernetes knowledge
  • Experience with GPUs and NVIDIA stack
  • Linux (Ubuntu) expertise
  • Experience with Terraform

Preferred Qualifications

  • Longhorn or Ceph experience
  • Canonical ecosystem (MAAS, Juju)
  • AI/ML tools like Kubeflow
  • Certifications (CKA, NVIDIA)

Soft Skills

  • Strong problem-solving and troubleshooting mindset
  • Ability to collaborate with cross-functional teams (ML engineers, data scientists)
  • Clear communication and documentation skills
  • Passion for automation and platform scalability

Key Responsibilities

  • Design and manage Kubernetes clusters
  • Build GPU-enabled infrastructure
  • Deploy Longhorn storage
  • Automate infrastructure using Terraform
  • Monitor systems using Prometheus and Grafana
  • Knowledge Transfer & Client Enablement
  • Provide structured knowledge transfer (KT) sessions to client teams on all core platform components, including:
    • Kubernetes architecture, operations, and troubleshooting
    • GPU infrastructure (NVIDIA stack, scheduling, resource optimization)
    • Longhorn storage management and performance tuning
    • Canonical ecosystem tools (MAAS, Juju, Charmed Kubernetes)
  • Develop and deliver technical documentation, runbooks, and training materials to support ongoing operations
  • Conduct hands-on workshops and guided sessions to enable client teams to independently manage and scale the platform
  • Act as a technical advisor, helping client stakeholders understand best practices in:
  • Cloud-native infrastructure
    o AI/ML platform operations
    o Reliability, performance, and cost optimization
  • Ensure smooth handoff of production systems with full operational readiness and support knowledge