Principal Cloud & AI Workload Performance Analysis Engineer

AMD
Austin
Workplace: HybridFull timeUSD 175,000 - 300,000 annuallyFunction: Data Science & Machine LearningEducation: bachelorsSkills: ["Technical writing","Presentation skills","Collaborating with external partners","Evidence-based communication"]

Own cloud-native and AI workload performance analysis for hyperscaler custom CPUs and next-generation AI systems. Build and maintain a workload taxonomy, design fair and reproducible benchmarking methods across CPU/accelerator platforms, and analyze host-CPU effects on accelerator utilization and end-to-end throughput. Develop performance-per-watt and price-performance models, track compiler/kernel/library and orchestration/migration factors, and deliver decision-ready technical and executive reports.

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FursaFursa
AMD
AMD
11 hours ago

Principal Cloud & AI Workload Performance Analysis Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 2 hours agoStatus: Live

Job Summary

Own cloud-native and AI workload performance analysis for hyperscaler custom CPUs and next-generation AI systems. Build and maintain a workload taxonomy, design fair and reproducible benchmarking methods across CPU/accelerator platforms, and analyze host-CPU effects on accelerator utilization and end-to-end throughput. Develop performance-per-watt and price-performance models, track compiler/kernel/library and orchestration/migration factors, and deliver decision-ready technical and executive reports.
Location: Austin
Workplace: Hybrid
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Define and maintain cloud-native and AI workload taxonomy for competitive analysis and forecasting.
  • •Design reproducible benchmarking methods for services, microservices, containers, scale-out data processing, caching, and supporting cloud/CPU functions.
  • •Compare AMD, Intel, Arm, and cloud-custom environments using aligned software versions, tuning policies, and service-level objectives.
  • •Analyze host-CPU impact on accelerator utilization, input pipelines, communication overheads, memory movement, NUMA behavior, and end-to-end throughput.
  • •Translate scaling behavior into 24–36 month forecast inputs and produce decision-ready technical and executive reports.

Pay and Benefits

Salary: USD 175,000 - 300,000 annually

Key Requirements

  • •Bachelors or Masters degree in electrical or computer engineering.
  • •Deep hands-on experience benchmarking and profiling cloud, distributed, or accelerated-system workloads.
  • •Strong Linux systems skills with proficiency in automation or scripting for deployment and analysis.
  • •Experience designing fair experiments across dissimilar CPU architectures and platform configurations.
  • •Ability to apply application profiling, hardware performance counters, and system telemetry to analyze AI host-side bottlenecks.
Education:Bachelor's in electrical or computer engineering
Skills:Technical writingPresentation skillsCollaborating with external partnersEvidence-based communication
Languages:English
Tech Stack:LinuxAutomationScriptingContainersOrchestrationMicroservicesWeb servicesNUMAMemory bandwidthInterconnectCPU-to-accelerator data movementPerformance benchmarkingPerformance profilingHardware performance countersSystem telemetryAI workloadsAI system throughputCompilerKernelLibraries

Eligibility

Work Authorization:Authorization required. Sponsorship not provided.

Company Brief

AMD
Designs and produces semiconductor products including CPUs, GPUs, and adaptive SoCs for consumer, enterprise, and embedded markets, competing across PCs, data centers, and gaming industries.
Industry: Electronics Manufacturing
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Santa Clara, United States
Founded: 1969
Glassdoor
Glassdoor: 3.9
WebsiteLinkedIn