Staff SoC Architect, AI Data Center

Job Title

Staff SoC Architect, AI Data Center

Role Summary

The Data Center AI Architecture team designs next-generation cloud AI SoCs and systems for generative AI inference. This role drives SoC, memory, and system architecture decisions across multiple product generations to meet performance, bandwidth, capacity, and scalability targets.

The position works cross-functionally with architecture, design, software, platform, product, and customer teams to define specifications, run architecture studies, and follow designs through implementation and production.

Experience Level

Senior. Preferred 7+ years of relevant experience in SoC, platform, or system architecture. Refer to Education Requirements for minimum experience tied to degree level; role also requires domain experience in system architecture technology areas.

Responsibilities

Deliver SoC and system architecture for data center AI products and drive analysis, tradeoffs, and implementation guidance.

• Translate product and workload requirements into SoC and system specifications and feature requirements.
• Execute quantitative SoC and system architecture studies and product definition; quantify tradeoffs across performance, power, area, cost, memory bandwidth, capacity, and scalability.
• Drive analysis methods and tools; develop high-level models, calculators, and simulation-based studies.
• Follow designs through implementation and production; correlate measured system performance with models, identify root causes of gaps, and drive performance closure.
• Perform competitive analysis across compute, memory, networking, software, and deployment considerations.
• Collaborate across architecture, design, software, platform, product, and customer teams; mentor technical contributors and generate technical innovations.

Requirements

Key technical and professional requirements. Education details are summarized separately below.

• Must-have: Proven experience in SoC and system architecture, including executing architecture studies and translating results into actionable recommendations.
• Must-have: Experience quantifying performance, power, area, cost, memory bandwidth, network topology/bandwidth/latency, and scalability tradeoffs.
• Must-have: Experience correlating modeled and measured system performance and driving cross-functional performance closure.
• Must-have: Strong technical communication and cross-team collaboration skills; ability to present to technical and business stakeholders.
• Nice-to-have: Experience with generative AI and ML workloads (LLM inference) and AI accelerator bottlenecks.
• Nice-to-have: Familiarity with DRAM and memory-controller architectures and protocols (LPDDR, HBM, DDR, GDDR) and emerging memory technologies.
• Nice-to-have: Knowledge of data center networking, RDMA, RAS/ECC, security, chiplets, PHYs, advanced packaging, power and thermal management, and system scalability.
• Nice-to-have: Programming for architecture modeling and automation; object-oriented C++ and Python preferred.
• Nice-to-have: Experience developing architecture methodologies, tools, and analysis frameworks.

Education Requirements

Minimum Qualifications specify one of the following: Bachelor's degree in Electrical Engineering, Computer Science, or a related field plus 4+ years of systems engineering or related work experience; OR Master's degree in Electrical Engineering, Computer Science, or a related field plus 3+ years of systems engineering or related work experience; OR PhD in Electrical Engineering, Computer Science, or a related field plus 2+ years of systems engineering or related work experience. Preferred qualifications list MS or PhD in EE, ECE, CE, CS, or related fields.

About the Company

Company: Qualcomm

Headquarters: San Diego, California, United States

Qualcomm is a global leader in semiconductor and telecommunications equipment, specializing in mobile technologies and innovations. Known for its Adreno GPUs, the company provides solutions enabling advancements in mobile gaming, AI, VR/AR, and autonomous driving. Qualcomm's cutting-edge technology and commitment to high-performance, power-efficient designs drive the evolution of mobile graphics and connectivity worldwide.