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Gpu Repair Jobs (NOW HIRING)

Job Summary We are seeking a highly accomplished experienced GPU Architect to define the next ... understand repair rates, SLAs, uptime curves. * NPI Manufacturing: The role requires a deep ...

Job Summary We are seeking a highly accomplished experienced GPU Architect to define the next ... understand repair rates, SLAs, uptime curves. * NPI Manufacturing: The role requires a deep ...

Principal Software Engineer, GPU Compute

San Mateo, CA · On-site

$153K - $206K/yr

Drive GPU reliability and performance at fleet scale, defining the detection, diagnosis, and automated repair of unhealthy accelerators before they impact production. * Evaluate and onboard new GPU ...

As an Debug Repair Technician you will: * Perform advanced board-level troubleshooting and ... GPU, FPGA, ASIC, memory, and power subsystems Diagnose high speed digital, power distribution, and ...

The Associate Product Manager will support and coordinate GPU-related operations across RMA, Service, Repair, Technical Support, and Production teams, with a focus on improving workflow efficiency ...

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Gpu Repair information

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$12

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$32

How much do gpu repair jobs pay per hour?

As of Jun 9, 2026, the average hourly pay for gpu repair in the United States is $21.41, according to ZipRecruiter salary data. Most workers in this role earn between $17.55 and $24.04 per hour, depending on experience, location, and employer.

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

To thrive as a GPU Repair Technician, you need a strong knowledge of computer hardware, electronics troubleshooting, and experience with soldering and component-level repair, often supported by relevant technical certifications or training. Familiarity with diagnostic tools, multimeters, oscilloscopes, and GPU testing software is typically required. Attention to detail, problem-solving skills, and effective communication help technicians accurately diagnose issues and explain solutions to clients. These skills ensure reliable GPU repairs, minimize downtime, and maintain customer trust in high-performance computing environments.

What are GPU repair services?

GPU repair services involve diagnosing and fixing issues with graphics processing units (GPUs) used in computers and gaming systems. Common problems include overheating, faulty memory chips, broken fans, or damaged solder joints. Technicians may clean the GPU, replace faulty components, or reflow/reball solder connections to restore functionality. Proper diagnostics are essential to determine whether repair or full replacement is more cost-effective. Reliable GPU repair can extend the device's lifespan and save money compared to purchasing a new graphics card.

What are some common challenges faced in GPU repair, and how can they be addressed?

Technicians working in GPU repair often encounter challenges such as diagnosing subtle hardware faults, dealing with delicate soldering work, and sourcing replacement components for discontinued models. Addressing these issues requires strong troubleshooting skills, familiarity with GPU architecture, and access to specialized tools like hot air rework stations and microscopes. Collaboration with other repair technicians and staying updated on manufacturer guidelines are also essential for successful repairs and ongoing professional development.

What is the difference between Gpu Repair vs Gpu Technician?

AspectGpu RepairGpu Technician
CertificationsHardware repair certifications, e.g., CompTIA A+Same as Gpu Repair, often includes electronics or hardware certifications
Work EnvironmentRepair shops, electronics labs, or service centersElectronics labs, repair shops, or manufacturing facilities
Job FocusDiagnosing and fixing GPU hardware issuesDiagnosing, repairing, and maintaining GPUs and related components
Industry UsageCommon in electronics repair industryUsed in electronics manufacturing and repair sectors

Gpu Repair and Gpu Technician roles overlap significantly, focusing on diagnosing and fixing GPU hardware issues. Gpu Technicians often have broader responsibilities, including maintenance and testing, but both require similar certifications and work environments. The main difference lies in scope: Gpu Repair is more specialized in hardware fixes, while Gpu Technicians may handle a wider range of electronic components.

More about Gpu Repair jobs
What cities are hiring for Gpu Repair jobs? Cities with the most Gpu Repair job openings:
What states have the most Gpu Repair jobs? States with the most job openings for Gpu Repair jobs include:
Infographic showing various Gpu Repair job openings in the United States as of May 2026, with employment types broken down into 2% As Needed, 19% Full Time, 61% Part Time, 3% Temporary, 10% Contract, and 5% Nights. Highlights an 99% Physical, and 1% Remote job distribution, with an average salary of $44,528 per year, or $21.4 per hour.

Other

Posted 7 days ago


Job description

About us

Graphcore is one of the world's leading innovators in Artificial Intelligence compute. 

It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry.  

As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world's most transformative technologies. We are opening a new AI Engineering Campus in Austin, which will play a central role in Graphcore's work building the future of AI computing!.  

Graphcore's teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. 

 

 

Job Summary

We are seeking a highly accomplished experienced GPU Architect to define the next generation of AI accelerators and multi-GPU cluster architecture. As the demand for trillion-parameter LLM training and high-throughput localized inference accelerates, the role of GPU architecture has never been more critical. In this role, you will lead the technology characterization, reliability, and interconnect performance strategies that ensure our compute fabrics scale flawlessly. You will collaborate deeply across hardware, firmware, and AI silicon teams to build GPU infrastructure capable of pushing the absolute limits of parallel processing and hardware efficiency.

Responsibilities and Duties

  • Hardware-Software Co-Design: Collaborate with software engineering to ensure the AI compute and Rack level hardware architectures fundamentally accelerate lower-level ML frameworks and localized inference engines (e.g., vLLM, Ollama, TensorRT).
  • Performance Modeling: Build and analyze cycle-accurate simulators and analytical models to identify bottlenecks, forecast workload performance, and guide architectural trade-offs.
  • Influence long-term silicon architecture roadmaps with our GPU SoC teams. Mentor engineering teams and drive strict engineering standards from feasibility to tape-out and post-silicon validation.  
  • Reliability: As a Platform level GPU architect, the role requires the candidate to have extensive knowledge in Reliability and Quality including but not limited to the ability to calculate MTBF, FIT rates, IEFR, IFR, and lifecycle bath-tub curves to understand repair rates, SLAs, uptime curves.
  • NPI Manufacturing: The role requires a deep knowledge with manufacturing processes to detect and correct any inadequate manufacturing frameworks that can impact the overall quality of the products we deploy in our Datacenters.

 

Candidate Profile

Essential:

  • Experience: 10+ years of deep experience in GPUs, AI accelerators, or highly parallel computer systems in areas of qualification, manufacturing, and programming.
  • Microarchitecture Expertise: Understanding of SIMD/SIMT execution models, instruction scheduling, and hardware acceleration for machine learning algorithms.
  • Manufacturing: Deep knowledge of advanced manufacturing techniques for build of AI compute units and Rack level L11 liquid cooled solutions.
  • Systems Interconnects: Extensive hands-on experience characterizing data pathways across RDMA environments, and hardware clustering protocols.
  • Programming & Tooling: Proficiency in C++, Python, or similar languages for performance modeling, GPU technology characterization, and workload profiling.
  • Analytical Rigor: Exceptional ability to characterize complex AI mathematical operations into efficient hardware implementations.
  • Education: BS or MS or equivalent experience in Computer Engineering or Electrical Engineering.

 

Desirable

  • Specific Topology Experience: Direct experience qualifying Rack-scale GPU designs including but not limited to NPI manufacturing, testing, quality and reliability calculations.

We welcome people of different backgrounds and experiences and are committed to building an inclusive work environment that makes Graphcore a great home for everyone. We are an equal opportunity employer and want to build a work environment where everyone is happy, productive and respectful so they can do their best work. If you have a disability or additional need that requires accommodation, just let us know.