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Gpu Performance Engineer Jobs in Mississippi (NOW HIRING)

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 Mississippi?

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

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

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

Network Engineer (Supercomputer Infrastructure) - Memphis

SpaceXAI

Southaven, MS

Full-time

Posted yesterday

New


SpaceX rating

8.7

Company rating: 8.7 out of 10

Based on 151 frontline employees who took The Breakroom Quiz

16th of 72 rated aerospace companies


Job description

SpaceXAI's mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company's mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates.

ABOUT THE ROLE:

SpaceXAI is looking for an exceptional network engineer with experience in mission-critical, large-scale production environments to support the design, build-out, and operation of networks that power our AI supercomputer campuses. As a member of the Supercomputer Infrastructure / Network Engineering team, you will provide design and operational support for the fabrics used by GPU training and inference clusters, site operations, automation and controls, and facilities teams. The ideal candidate thrives in intense, high-flux environments, brings a strong sense of urgency balanced with operational excellence, communicates clearly, and demonstrates high technical acumen.

RESPONSIBILITIES:
  • Design and implement highly available, low-latency, high-bandwidth networks, carefully balancing routing, congestion control, and redundancy technologies for AI training fabrics, inference front-ends, storage, and site/OT networks.
  • Design and maintain supercomputer data center and campus networks in accordance with company network standards. Collaborate with adjacent infrastructure, compute, storage, SiteOps, and enterprise teams.
  • Evaluate, procure, and deploy network hardware including data-center class switches, NICs, firewalls, optical multiplexers, and related appliances supporting 400G/800G and beyond.
  • Contribute to maturing network automation tooling; implement configuration analysis, linting, validation, and scalable deployment frameworks (GitOps / IaC).
  • Plan and coordinate network change windows with stakeholders to perform software updates, hardware refreshes, cluster expansions, and general maintenance (including evenings and weekends when required by compute schedules).
  • Troubleshoot and resolve network-related issues affecting cluster health and job performance; publish root cause analysis (RCA) documentation and host retrospectives.
  • Provide direct networking support during cluster bring-up, expansion, and production training/inference campaigns; serve as on-call or networking responsible engineer during operations.
  • Proactively tailor network monitoring and telemetry (fabric health, congestion, packet loss, NCCL/collective performance) so issues are detected before they impact training or inference.
  • Continuously create and update network documentation, including architecture overviews, design drawings, fiber/cable plant records, and operational procedures.
  • Collaborate with cross-functional teams to identify and resolve potential design issues, especially systemic or cascading failure modes and false redundancy in AI fabrics and site networks.
  • Perform job walks with customers, vendors, and contractors to gather requirements and produce implementation plans for new halls, rows, and campus interconnects.
  • Ensure networks are configured and maintained in compliance with industry and cybersecurity standards (e.g., ITAR, ISO, NIST), with particular attention to segmentation between compute fabrics, storage, OT/controls, and corporate networks.
BASIC QUALIFICATIONS:
  • Bachelor's degree in computer science, computer engineering, or other STEM discipline and 3+ years of professional network engineering experience;
    • OR 5+ years of professional network engineering experience in lieu of a degree.
  • Extensive hands-on experience designing, deploying, supporting, and troubleshooting Layer 2 and Layer 3 networks in latency-sensitive and/or industrial / data-center environments.
  • Functional experience with multiple network vendors in production or lab environments.
  • Experience with GitOps and Infrastructure as Code frameworks, both as a user and contributor.
PREFERRED SKILLS AND EXPERIENCE:
  • Strong understanding of the OSI model and network standards.
  • Hands-on experience with Cisco, Arista, Juniper, and/or NVIDIA Spectrum-X data-center class switches.
  • Experience with RoCEv2 Ethernet AI/HPC fabrics; InfiniBand experience is a plus.
  • Working knowledge of AI training and inference traffic patterns and how they behave on the network (collectives, congestion, ECMP, adaptive routing). Familiarity with NCCL is a plus.
  • Experience with WDM and large-scale single-mode / multimode fiber plants, including OTDR and acceptance testing.
  • Experience with switch port security, network segmentation, QoS, multicast, and redundancy protocols.
  • Familiarity with network monitoring and Layer 1 test tools; experience building operational telemetry and dashboards.
  • Proficiency in scripting (Bash / PowerShell / Python) and automation frameworks (Terraform, Ansible, etc.).
  • Linux and Windows system administration experience professionally or from labs.
  • Industry-standard certifications such as CCNA or CCNP.
  • Experience supporting real-time systems, industrial control / OT networks, or high-reliability environments in data center, energy, aerospace, defense, or similar industries.
  • Excellent communication skills with internal and external customers, vendors, and management in both formal and informal settings.
ADDITIONAL REQUIREMENTS:
  • Ability to pass applicable background checks for site access.
  • Ability to work in tight quarters; physical dexterity is necessary to perform job functions.
  • Availability for extended hours and/or weekends as the schedule varies with cluster build-out and operational needs; flexibility is required.
  • Ability to provide 24x7 on-call support in emergency situations and participate in an after-hours on-call rotation.
  • Willingness to travel (up to 20%) between supercomputer campuses and related sites.
  • Ability to lift 30 lbs.
  • Ability to work at heights.
  • Ability to drive (active valid driver's license).

SpaceXAI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice.


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About SpaceX

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Industry

Aerospace product and parts manufacturing, data services, guided missile and space vehicle manufacturing and satellite telecommunications

Company size

1,001 - 5,000 Employees

Headquarters location

Hawthorne, CA, US