We are seeking a highly skilled engineer to enable highly optimized mapping of AI workloads to Qualcomm’s next generation system-technology solutions for the slowing Moore’s law era. The focus is on identifying the system and technology bottlenecks for the state-of-the-art and emerging AI workloads e.g. the mixture-of-experts (MoE), multi-tenant vector databases, multimodal physical AI etc.. The E2E system KPIs for mapping these emerging AI workloads include the power, performance and TCO of the entire system encompassing the SoC, memory and networking. The primary role of the candidate is to map the workloads using both internal and external tools to Qualcomm’s next-gen AI accelerator systems and carry out what-if scenarios of optimizing different underlying components e.g. SoC, memory, networking and other technology features for the best power-performance-TCO trade-off. The candidate also needs to ensure which AI workloads are relevant for the different business units (BUs) from datacenters to physical AI to computing devices. To drive these technologies the person will collaborate with high-level representatives across functional teams (e.g. Architecture, product management, SW teams) to enable an implementation strategy that meets system requirements.
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Job Type
Full-time
Career Level
Senior
Number of Employees
5,001-10,000 employees