Qualcomm's Cloud AI Data Center Architecture team is defining the next-generation cloud AI data center products to serve Large Language Model and Generative AI inference workloads, which demand exceptional effective memory bandwidths & capacities for effective compute.
Requirements
- Computer architecture background and the quantitative analysis tools and methods
- Analytical, behavioral, functional, and performance modeling and analysis
- Simulator architectures and frameworks (C++ or Python-based preferred)
- Background in memory systems, understanding the tradeoffs among bandwidth, latency, power, etc.
- Understanding of DRAM memory organization and architecture, memory controllers & scheduling across one or more protocols such as LPDDR, HBM, DDR, GDDR, etc.
- Record of quantitative analysis using (and developing) tools such as high-level calculators & spreadsheets, DRAM timing simulators, profilers, functional and performance simulators, etc.
- Ability to abstract appropriately to define problems and solutions, and make data-driven decisions
Responsibilities
- innovate, analyze, and help define multiple generations of AI acceleration and memory system solutions
- engage with Cloud BU architects to understand product requirements
- analyze accelerator and memory technologies
- quantify tradeoffs
- influence the technical direction with data-driven justification
- effectively communicate and collaboratively engage with the other SoC & IP architects, designers, systems engineers, product managers, and software teams to enable market-leading Cloud AI and Data Center products.
Other
- Bachelor's degree in Electrical Engineering, Computer Science, or related field and 4+ years of Systems Engineering or related work experience.
- Master's degree in Electrical Engineering, Computer Science, or related field and 3+ years of Systems Engineering or related work experience.
- PhD in Electrical Engineering, Computer Science, or related field and 2+ years of Systems Engineering or related work experience.
- Excellent communication, documentation, and interpersonal skills with ability to convey proposals and interact effectively across a distributed multi-discipline organization
- Self-driven execution and a focus on accuracy and rigorous methodology
