Performance Engineering Architect
Hewlett Packard Enterprise (HPE)Match Score
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Protocol Intelligence
Data-driven signals on your job's competitivenessTier-1 brand plus Bengaluru location increases applicant density despite niche GPU performance specialization.
Requires specialized AI/GPU server performance expertise, limiting cross-industry transferability.
Extensive mandatory GPU/AI performance skills, tooling, and hardware expertise create strict shortlisting filters.
Job Description
Structured overview of role & requirementsAbout This Role
Lead performance characterization and optimization of AI solutions across GPUs, servers, storage, networking, and system software.
Design and execute benchmarking studies for generative AI, ML workloads; produce performance reports and recommendations supporting product design and customer decisions.
Develop and automate benchmarks, analyze telemetry, and collaborate cross-functionally with engineering, product, sizing, and partner teams.
Minimum Requirements
Strong expertise in generative AI and ML performance, with hands-on experience benchmarking AI workloads on GPU-accelerated systems.
Proficiency in Linux administration, Python and shell scripting for automation, and working knowledge of AI performance tools and telemetry platforms.
Deep understanding of server hardware architecture (CPU, GPU, NUMA, PCIe, storage, networking) and experience configuring/troubleshooting enterprise servers.
Work Experience Required: Not explicitly mentioned in the JD; Role requires onsite work from an HPE office.
Ideal Candidate Profile
Experienced in detailed system-level performance analysis spanning hardware and software stack to identify bottlenecks and optimize AI workloads.
Skilled in establishing scalable, repeatable performance test methodologies and automating measurement pipelines for AI inference and training.
Able to communicate complex performance insights to diverse stakeholders and collaborate effectively across engineering, product, and field teams.