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HPC & AI Performance Engineer
Hewlett Packard Enterprise. Lead HPC and AI benchmarking projects across CPU, GPU, network, memory, and storage platforms .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in HPC and AI benchmarking, including performance analysis and optimization of complex workloads across various platforms. Proficient in translating technical findings into actionable recommendations for stakeholders.
Highest-signal resume keywords
HPC And AI WorkloadsPerformance Profiling ToolsParallel And Distributed Programming TechniquesNVIDIA GPUs And AMD Instinct MI-Series AcceleratorsC, C++, Fortran, Python
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
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Hard Skills
Performance AnalysisApplication OptimizationBenchmarkingParallel ComputingGPU AccelerationLinux-Based SystemsAI FrameworksCompilersMemory OptimizationI/O Optimization
Soft Skills
Analytical SkillsProblem-Solving SkillsWritten CommunicationVerbal Communication
Tools & Technologies
CUDAHIPMPIOpenMPOpenSHMEMOpenACCPerformance-Profiling ToolsTracing ToolsDebugging Tools
Industry Keywords
HPC ArchitectureAI Training And InferenceLarge Language ModelsScientific ApplicationsEngineering Applications
Tech Stack
Tools & technologiesLinuxPythonC++
About the role
Key responsibilities & impact- Lead HPC and AI benchmarking projects across CPU, GPU, network, memory, and storage platforms
- Evaluate HPE and competitive HPC and AI architectures using performance models and benchmark data
- Run and analyze scientific, engineering, large language model, AI training and inference, storage, and I/O workloads
- Identify performance bottlenecks and optimize applications, AI frameworks, libraries, compilers, runtimes, and system software
- Apply parallel computing, GPU acceleration, profiling, and memory and I/O optimization to deliver credible, repeatable results
- Present complex technical findings clearly to engineering teams, customers, and business stakeholders
- Translate performance findings into customer-focused recommendations
Requirements
What you’ll need- 6+ years of experience with HPC and AI workloads, including scientific and engineering applications, MLPerf, large language models such as DeepSeek, Kimi K2.6 or K3, and gpt-oss-120b, AI training and inference, storage benchmarks, and performance-profiling tools; relevant coursework and internship experience will be considered
- Knowledge of HPC and AI system architecture, including CPUs, GPUs and other accelerators, memory, networking, storage, and software stacks
- Understanding of parallel and distributed programming techniques, including MPI, OpenMP, OpenSHMEM, and algorithms
- Ability to lead complex HPC and AI performance projects and translate findings into customer-focused recommendations
- Demonstrated ability to analyze and optimize computational applications and benchmarks on Linux-based HPC and AI systems
- Experience with C, C++, Fortran, Python, Linux scripting, compilers, MPI, MPI-IO, OpenMP, and relevant AI frameworks and libraries
- Experience with NVIDIA GPUs and AMD Instinct MI-series accelerators, including CUDA, HIP, OpenMP target offload, OpenACC, or comparable programming models
- Experience using performance-profiling, tracing, and debugging tools on Linux-based HPC and AI systems
- Ability to interpret benchmark results, identify performance bottlenecks, and recommend improvements
- Excellent analytical and problem-solving skills
- Excellent written and verbal communication skills
- Professional proficiency in English required
- Master’s degree in computer science, engineering, mathematics, physics, chemistry, environmental science, or a related technical field
- PhD preferred
Benefits
Comp & perks- Comprehensive health and wellbeing benefits supporting physical, financial and emotional wellbeing
- Personal and professional development programs
- Flexible work arrangements to manage work and personal needs
- Inclusive workplace
- Reasonable accommodation during the application or interview process for applicants with disabilities