System Validation Engineer
Solidigm
System Validation Engineer
Solidigm
Designs and manufactures enterprise SSDs
The successful candidate will lead complex validation, debugging, and failure analysis activities for enterprise Solid State Drives (SSDs). This role will work closely with validation, firmware and architecture teams to ensure world-class product quality, reliability, and customer satisfaction. The engineer will be responsible for driving root cause investigations of issues from validation and integration failures, defining debug strategies, improving validation methodologies, and influencing future product designs through data-driven insights. The role requires technical expertise in storage technologies, deep system-level debugging, and validation engineering. In addition to validation activities, the candidate will contribute to automation initiatives, debug tool development, test framework improvements, and advanced analytics solutions that increase engineering efficiency and accelerate issue resolution.
Education: Bachelor’s Degree or higher in Electrical Engineering, Computer Engineering, Computer Science, Software Engineering, or a related technical discipline.
Required Qualifications:
Preferred Qualifications:
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Solidigm designs and manufactures NAND flash memory and enterprise SSDs for data centers, cloud, and AI workloads. Its product line includes high-density QLC drives and liquid-cooled eSSDs for fanless GPU servers, plus software like CSAL (Cloud Storage Acceleration Layer) and the Luceta AI vision software suite. It operates as a standalone subsidiary within SK hynix, with R&D in Rancho Cordova, and serves enterprises, cloud providers, data-center operators, and storage solution providers. Unlike many rivals, Solidigm combines a broad range of form factors and capacities with open-source storage acceleration software and AI-focused tooling, supported by a corporate structure that aligns with SK hynix’s AI investment strategy. The goal is to provide reliable, scalable storage solutions for data centers, cloud infrastructure, AI infrastructure, and edge deployments, helping customers store and access large amounts of data efficiently.
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