{"schemaVersion":"jobsearcher.job.v1","id":"09d64e175a9526bc637abb7e","url":"https://jobsearcher.com/jobs/09d64e175a9526bc637abb7e","canonicalUrl":"https://jobsearcher.com/jobs/09d64e175a9526bc637abb7e","title":"Software Engineer, Compute Performance","description":"Software EngineerCisco Validated Infrastructure Services (CVIS) establishes and proves the performance of large AI clusters before they are handed over to customers. We deploy each cluster, validate it against performance baselines, and deliver the evidence that it is ready for service. The platform behind that work is full stack. It combines workflow and API services, network and infrastructure automation, and the UI used to run validation across labs and customer environments.As a Software Engineer, you will help analyze and improve the performance of AI compute systems across hardware, system software, and application workloads. In this role you will:Run and analyze AI training, inference, and HPC workloads on GPU-accelerated systems.Investigate compute, memory, PCIe, storage, and workload scaling issues.Use telemetry, logs, traces, and profiling tools to identify performance bottlenecks.Develop automation for performance testing, regression detection, and failure triage.Work with hardware and software teams to resolve system and workload performance issues.Document findings, test procedures, and performance results.Minimum QualificationsBachelor's degree with + 5 years of related experience, or Master's degree with + 3 years of related experience, or PhD with relevant research experience, or equivalent related work experience.Experience debugging, testing, or tuning Linux-based systems.Experience running or evaluating AI, machine learning, or HPC workloads.3 + years of experience with a programming or scripting language such as Python, C, C++, Go, or Bash.Preferred QualificationsFamiliarity with GPU computing technologies such as CUDA, ROCm, NCCL, or RCCL.Familiarity with performance tools such as Nsight, DCGM, rocprofiler, or similar tools.Understanding of GPU system components such as memory, NUMA, PCIe, and scale-up interconnects.Exposure to NVIDIA NVLink and NVSwitch or AMD Infinity Fabric/xGMI.Experience with Kubernetes, Slurm, or other distributed workload environments.Strong ownership, documentation, and cross-team collaboration skills.","company":"Webex Events Formerly Socio","rawCompany":"webex events formerly socio","city":"Milpitas","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-10-05T13:13:51.754Z","occupations":[{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1299.00","title":"Computer Occupations, All Other","slug":"computer-occupations-all-other"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"518210","title":"Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services","slug":"computing-infrastructure-providers-data-processing-web-hosting-and-related-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Software Engineer, Compute Performance","description":"Software EngineerCisco Validated Infrastructure Services (CVIS) establishes and proves the performance of large AI clusters before they are handed over to customers. We deploy each cluster, validate it against performance baselines, and deliver the evidence that it is ready for service. The platform behind that work is full stack. It combines workflow and API services, network and infrastructure automation, and the UI used to run validation across labs and customer environments.As a Software Engineer, you will help analyze and improve the performance of AI compute systems across hardware, system software, and application workloads. In this role you will:Run and analyze AI training, inference, and HPC workloads on GPU-accelerated systems.Investigate compute, memory, PCIe, storage, and workload scaling issues.Use telemetry, logs, traces, and profiling tools to identify performance bottlenecks.Develop automation for performance testing, regression detection, and failure triage.Work with hardware and software teams to resolve system and workload performance issues.Document findings, test procedures, and performance results.Minimum QualificationsBachelor's degree with + 5 years of related experience, or Master's degree with + 3 years of related experience, or PhD with relevant research experience, or equivalent related work experience.Experience debugging, testing, or tuning Linux-based systems.Experience running or evaluating AI, machine learning, or HPC workloads.3 + years of experience with a programming or scripting language such as Python, C, C++, Go, or Bash.Preferred QualificationsFamiliarity with GPU computing technologies such as CUDA, ROCm, NCCL, or RCCL.Familiarity with performance tools such as Nsight, DCGM, rocprofiler, or similar tools.Understanding of GPU system components such as memory, NUMA, PCIe, and scale-up interconnects.Exposure to NVIDIA NVLink and NVSwitch or AMD Infinity Fabric/xGMI.Experience with Kubernetes, Slurm, or other distributed workload environments.Strong ownership, documentation, and cross-team collaboration skills.","datePosted":"2026-10-05T13:13:51.754Z","dateModified":"2026-10-05T13:13:51.754Z","hiringOrganization":{"@type":"Organization","name":"Webex Events Formerly Socio","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Milpitas","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"09d64e175a9526bc637abb7e"},"url":"https://jobsearcher.com/jobs/09d64e175a9526bc637abb7e"}}