Principal Engineer - Memory-Centric AI Compute Architect
About The Position
The Qualcomm Memory System/Technology Team in Process & Package Solutions Group has an opening in the areas of AI workload mapping to the memory-centric compute systems for data center, mobile, compute, and XR. The candidate will develop new algorithms and architectures that move computation closer to or directly into memory to overcome the performance bottleneck of data transfer between processors and memory. The candidate should have good knowledge of bus and compute fabrics as well as state-of-the-art AI models such as LLM, transformers, CNN, etc. This role involves creating and optimizing AI models for memory-centric systems by designing algorithms and hardware modules that improve speed, power efficiency, and scalability of those AI workloads. This position offers the opportunity to work across multiple organizations such as process and packaging team, AI and compute architects, memory controller team, global SoC team, and emulation team. Providing timely feedback and updating architecture and design trade-offs to the team is essential.
Requirements
- Bachelor's degree in Science, Engineering, or related field and 8+ years of ASIC design, verification, validation, integration, or related work experience.
- Master's degree in Science, Engineering, or related field and 7+ years of ASIC design, verification, validation, integration, or related work experience.
- PhD in Science, Engineering, or related field and 6+ years of ASIC design, verification, validation, integration, or related work experience.
- Experience in computer and memory architectures
- Good knowledge of AI models such as CNNs, RNNs, transformers, LLM, multi-modal AI, and AI agents
- Good knowledge of dataflow, memory and bus protocols
- Knowledge of tensor cores, near-memory computing, and high-bandwidth memories such as HBM
- Knowledge in memory controller design
- Proficiency in use of performance modeling tools
- Good knowledge of memory architecture, scalar processors, and 2.5D/3D integration
- Master's or Ph.D. in Electrical Engineering, Computer Science, and a related field
- Good communication skills
- Strong teamwork
- Strong problem-solving and analytical skills
- Ability to work independently and as part of a team
Nice To Haves
- Familiar with in/near-memory computing
- Experience in programming language (C/C++/Phyton) or scripting language (Perl/Python)
- Familiar with the DRAM datasheets and IO interfaces
Responsibilities
- Architect, design, and implement scalable AI/ML computing infrastructure for data center, compute, and mobile
- Develop and optimize AI algorithms for the memory-centric compute systems for better performance and power
- Co-optimize compute, memory, and connect fabric allocation for the improved scale-up and scale-out metrics
- Develop and validate the algorithms using Phyton, C, etc for improved throughput, latency, power, and energy
- Use state-of-the-art modeling tools and numerical analysis techniques for performance modeling
Benefits
- competitive annual discretionary bonus program
- opportunity for annual RSU grants
- highly competitive benefits package
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What This Job Offers
Job Type
Full-time
Career Level
Principal
Education Level
Ph.D. or professional degree
