Senior SoC Performance Architect

Qualcomm•Austin, TX

About The Position

We are seeking a Senior SoC Performance Architect to lead server CPU workload analysis, performance modeling, competitive projection, and optimization across both hardware and software. This role is focused on understanding end-to-end system performance for complex server workloads, identifying bottlenecks across the compute stack, and driving actionable improvements in CPU, memory, fabric, I/O, firmware, OS, compiler, and application behavior. The ideal candidate combines deep architectural knowledge with strong analytical rigor and hands-on performance debugging experience. In this role, you will work across architecture, design, software, systems, and partner organizations to evaluate current and future SoC products, build performance insights, and guide product and feature decisions. You will be expected to enable and analyze complex server workloads on internal platforms, develop analytical and empirical performance models, perform sensitivity studies, and project performance for both internal designs and external competitive products.

Requirements

PhD in Computer Engineering, Electrical Engineering, Computer Science, or related field, with 5+ years of industry experience in CPU performance modeling and analysis.
Deep understanding of CPU microarchitecture, including pipelines, OoO execution, branch prediction, caches, prefetching, SMT, and performance bottlenecks.
Strong knowledge of SoC-level architecture, including on-chip fabric/interconnect, memory controllers, DRAM systems, coherency, and I/O subsystems.
Deep understanding of operating systems and compilers, including scheduling, memory management, synchronization, code generation, optimization behavior, and runtime effects on performance.
Hands-on experience with performance analysis tools such as perf, Intel VTune, and AMD uProf.
Strong experience in workload analysis, performance characterization, modeling, projection, and optimization for server-class systems.
Experience enabling and debugging complex server workloads in Linux-based environments.
Strong analytical, scripting, and data analysis skills for handling large profiling datasets and developing performance models.
Demonstrated ability to work across organizational boundaries and influence both hardware and software roadmaps through data-driven analysis.
Bachelor's degree in Electrical Engineering, Computer Science, or related field and 6+ years of Systems Engineering or related work experience.
Master's degree in Electrical Engineering, Computer Science, or related field and 5+ years of Systems Engineering or related work experience.
PhD in Electrical Engineering, Computer Science, or related field and 4+ years of Systems Engineering or related work experience.
2+ years of experience in one or more system architecture technology areas and products (e.g., Power System, Shared Resource Management, Limits/Thermal Management, Hardware Islands).

Nice To Haves

Experience with pre-silicon performance modeling, simulation, or trace-based analysis.
Experience with server workloads spanning cloud, enterprise, data analytics, web, database, virtualization, and AI infrastructure.
Experience with competitive performance analysis and product projection methodologies.
Familiarity with PMU-based top-down analysis, CPI decomposition, memory subsystem analysis, and sensitivity modeling.
Experience working with firmware, BIOS, power/performance tuning, and system configuration controls.
Experience presenting architectural recommendations to senior technical leadership.

Responsibilities

Drive workload-based performance analysis for server SoCs, with emphasis on CPU-intensive and system-level workloads.
Enable, run, and characterize complex server workloads on pre-silicon and post-silicon platforms.
Perform detailed bottleneck analysis across CPU cores, caches, memory hierarchy, on-chip fabric, memory controllers, and I/O subsystems.
Build analytical and empirical models for workload behavior, performance scaling, and feature sensitivity.
Develop performance projections for internal products and competitive external products.
Conduct sensitivity studies to hardware and software parameters such as frequency, cache size, memory latency/bandwidth, prefetch behavior, SMT, compiler options, scheduling, and system configuration.
Identify optimization opportunities across both hardware and software, and drive recommendations to architecture, design, compiler, OS, firmware, and application teams.
Partner closely with hardware and software organizations to root-cause performance gaps and drive cross-functional optimization plans.
Define methodologies, metrics, and KPI frameworks for workload analysis, performance tracking, and feature evaluation.
Use profiling and performance monitoring tools to collect PMU data, hotspot profiles, call stacks, CPI breakdowns, memory behavior, and microarchitectural stall analysis.
Summarize findings for technical and executive audiences, including architecture tradeoffs, product implications, and competitive positioning.