VP of Information Systems at Coralogix
Coralogix
Lead Coralogix’s information systems strategy, enterprise applications, integrations, and governed data platform. Advance automation and AI adoption across its AI-powered observability business.
Open
Xora Innovation is a venture capital firm backing deep tech entrepreneurs working to reshape essential industries. Its investments span three areas: compute and communications, climate and energy, and AI applied to physical industries. Xora supports companies developing technologies for the infrastructure of the future.
Head of Memory Architecture at Xora Innovation
Lead purpose-built memory architecture for agentic AI inference and data center computing. Optimize memory systems, workloads, and PPAC trade-offs as the product moves toward commercialization.
Description
- Lead architecture for purpose-built memory designed for AI inference computing.
- Design, model, and optimize memory subsystems for a new memory category and product.
- Balance memory footprint, bandwidth, latency, power efficiency, density, silicon area, and cost per bit.
- Design memory vaults and hierarchies, on-chip interconnects, sense amplifiers, and address translation.
- Analyze agentic AI inference applications, software, models, and advanced SoCs for data center workloads.
- Benchmark advanced AI inference SoC architectures and workload management against competing memory architectures and devices.
- Apply knowledge of core materials and device technology to novel bit-cell and device architectures.
- Work with SoC architects, NPI teams, silicon design, and technology teams to speed the product’s path to market.
- Promote the memory offering and build understanding through industry and academic networks.
Requirements
- A master’s or Ph.D. in computer science, computer engineering, or electrical engineering is preferred.
- At least 10 years of memory architecture experience, preferably at a leading memory IDM.
- Strong understanding of current memory issues and challenges, especially for agentic AI inference computing.
- Experience with power, performance, area, and cost (PPAC) analysis and modeling.
- A broad network of relevant industry and academic experts.
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