Senior DDR and Execution Validation Engineer
Graphcore
Senior DDR and Execution Validation Engineer
Graphcore
Delivers IPU-powered AI cloud services
Job Summary
Reporting to the Memory Validation leadership team, the Senior Silicon DDR/HBM Validation Engineer will be responsible for the bring-up, validation, characterization and debug of advanced memory subsystems used in next-generation AI compute platforms.
The role will focus on DDR and HBM technologies, working closely with silicon design, firmware, characterization, platform and systems teams to ensure robust memory subsystem functionality, performance and reliability. The successful candidate will take ownership of significant validation activities, contribute to debug and root-cause analysis efforts, and help improve validation methodologies, automation and infrastructure.
The Team
The Memory Validation team sits within the Validation organisation and is responsible for the bring-up, validation, characterization and debug of memory subsystems across Graphcore silicon and platform products.
The team supports DDR and HBM validation activities throughout the product lifecycle, from first silicon through production readiness. Engineers work closely with architecture, RTL, firmware, characterization, systems and platform teams to ensure memory technologies meet functionality, performance, reliability and performance objectives.
Responsibilities and Duties
Candidate Profile
Essential
Desirable
Graphcore.ai focuses on building and delivering Intelligence Processing Units (IPUs) and related AI services for enterprises. It provides IPU-powered cloud services, pre-trained AI models, optimized inference engines, and APIs on a subscription basis with on-demand pricing and free tiers through cloud partners. The IPUs accelerate AI workloads and enable scalable, cost-efficient AI deployment in enterprise applications. The company differentiates itself through specialized IPU hardware and optimized software stack, plus partnerships with cloud providers to reach customers, rather than relying on generic hardware. The goal is to help businesses scale AI-powered products and operations efficiently by offering flexible, scalable compute and ready-to-use AI components.
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