THE ROLE
The Storage Benchmarking Engineer will design, execute, and analyze performance benchmarks using industry-standard tools like fio, vdbench, SPEC SFS 2020, IO500, MLPerf, and more. This role demands strong end-to-end performance troubleshooting skills across the entire stack (compute, network, and storage), along with collaboration with engineering, product management, marketing, and sales teams. The ideal candidate will have experience engaging with benchmark standards organizations and communities, exceptional communication and writing skills.
WHAT YOULL DO
Configure HPC lab environment so all systems can achieve maximum efficiency and scale to support a variety of different test harnesses. This includes robust automation to ensure labs can be rapidly configured/reconfigured to meet a variety of different benchmarks.
Design and execute storage performance benchmarks using industry-standard benchmarks, including fio, vdbench, SPEC SFS 2020, IO500, MLPerf, SPC-1/SPC-2 (or similar benchmarks).
Perform end-to-end performance troubleshooting and debugging across compute, network, and storage components to pinpoint and resolve bottlenecks and achieve the best possible results.
Develop and maintain automated benchmarking workflows using tools like Ansible, Python, or Bash to ensure rapid provisioning and efficient, repeatable, and reproducible test results.
Analyze benchmark results, generate detailed reports, and provide actionable insights to engineering teams for product optimization.
Collaborate with engineering, product management, marketing, and sales to align benchmarking efforts with product goals and customer needs.
Engage directly with benchmark standards organizations (e.g., SPEC, SNIA, MLCommons) and communities to influence methodologies and stay ahead of industry trends.
Deliver high-impact presentations to internal teams, customers, and external stakeholders, translating complex technical data into clear narratives.
Write technical marketing documents, whitepapers, and performance summaries to support product launches and customer engagement.
Maintain comprehensive documentation of benchmarking processes, configurations, and results.
We are primarily an in-office environment and therefore, you will be expected to work from the Santa Clara office in compliance with Everpure's policies, unless you are on PTO, or work travel, or other approved leave.
WHAT YOU BRING
Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field (or equivalent experience).
5+ years of experience in storage performance benchmarking or a related technical role.
Proven expertise with storage benchmarking tools, including:
• fio: Flexible I/O tester for workload simulation • vdbench: Versatile storage benchmarking tool for enterprise workloads • Standard Performance Evaluation Corporation (SPEC) Spec Sfs2020
Strong end-to-end performance tuning and troubleshooting skills across the entire stack include compute, network, and storage layers.
Hands-on experience with automation tools (e.g., Python, Ansible, Bash) for test orchestration and data collection.
Demonstrated track record of interfacing with engineering, product management, marketing, and sales teams.
Direct engagement with benchmark standards organizations (e.g., SPEC, SNIA, MLCommons etc) and storage benchmarking communities.
Exceptional communication skills, with proven ability to deliver engaging technical briefs and presentations to technical and non-technical audiences.
Strong writing skills, ideally with experience authoring technical marketing documents, whitepapers, or performance summaries.
Proficiency in data analysis and visualization tools (e.g., Python, R, sheets, Excel, Tableau etc).
Deep understanding and hands-on proficiency with enterprise storage technologies (e.g., NVMe, SSDs, and scale up and scale out block/file/object storage, distributed systems).
Experience with Everpure Storage products (e.g., FlashArray, FlashBlade) or similar enterprise block, file and object storage platforms.
Familiarity with cloud storage (e.g., AWS S3, Azure Blob, Google Cloud Storage) or HPC environments.
Knowledge of containerized benchmarking workflows using Docker or Kubernetes.
Prior contributions to benchmark standards or open-source performance tools.