Hewlett Packard Enterprise
Hewlett Packard Enterprise
Hewlett Packard Enterprise izstrādā uzņēmumu tehnoloģijas organizācijām, kas izmanto hibrīdās mākoņvides un mākslīgā intelekta vadītus procesus. Tās produktu klāstā ietilpst HPE ProLiant serveri un HPE Cray augstas veiktspējas skaitļošanas risinājumi, HPE Alletra datu glabāšanas risinājumi, HPE Aruba tīklu risinājumi, mākslīgā intelekta platformas un pilnībā gatavas mākslīgā intelekta rūpnīcas, kā arī GreenLake risinājumi kā pakalpojums. HPE nodrošina arī tādas drošības iespējas kā Zero Trust un SASE, kā arī profesionālos, konsultāciju un atbalsta pakalpojumus, kas palīdz lielām organizācijām modernizēt infrastruktūru, pārvaldīt datu centru vidi un ieviest mākslīgo intelektu plašā mērogā.

HPC and AI Performance Engineer at HPE (Houston Hybrid)

Lead benchmarking and optimization across CPU, GPU, network, memory, and storage architectures for HPC and AI workloads. Deliver repeatable performance analysis and practical recommendations for customers and engineering teams.

Apraksts

  • Direct HPC and AI benchmarking initiatives across CPU, GPU, network, memory, and storage platforms
  • Assess HPE and competing HPC and AI architectures using performance models and benchmark evidence
  • Execute and evaluate scientific, engineering, large language model, AI training and inference, storage, and I/O workloads
  • Diagnose bottlenecks and improve applications, AI frameworks, libraries, compilers, runtimes, and system software
  • Use parallel computing, GPU acceleration, profiling, and memory and I/O tuning to produce reliable, repeatable results
  • Explain complex technical conclusions clearly to engineers, customers, and business stakeholders
  • Convert performance analysis into recommendations tailored to customer needs

Prasības

  • At least 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 internships may also be considered
  • Knowledge of HPC and AI architectures spanning CPUs, GPUs and other accelerators, memory, networking, storage, and software stacks
  • Understanding of parallel and distributed programming methods, including MPI, OpenMP, OpenSHMEM, and algorithm design
  • Ability to lead complex HPC and AI performance initiatives and turn results into customer-oriented recommendations
  • Proven ability to analyze and optimize computational applications and benchmarks on Linux-based HPC and AI platforms
  • 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 using CUDA, HIP, OpenMP target offload, OpenACC, or comparable programming models
  • Experience with profiling, tracing, and debugging tools for Linux-based HPC and AI systems
  • Ability to interpret benchmark data, locate performance constraints, and recommend improvements
  • Strong analytical and problem-solving abilities
  • Strong written and verbal communication skills
  • Professional proficiency in English
  • Master’s degree in computer science, engineering, mathematics, physics, chemistry, environmental science, or a related technical discipline
  • PhD preferred

Priekšrocības

  • Comprehensive health and wellbeing coverage addressing physical, financial, and emotional wellbeing
  • Programs supporting personal and professional growth
  • Flexible working arrangements for balancing professional and personal responsibilities
  • Inclusive workplace environment
  • Reasonable accommodations during the application or interview process for applicants with disabilities

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