Systems Architect: Memory Wall Exploration
HP Development Company, L.P. - Spring, TX
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Systems Architect: Memory Wall Exploration Description - Job Summary: The Systems Architect: Memory Wall Exploration focuses on understanding how AI execution interacts with platform resources, particularly memory hierarchy, data movement, and shared-memory behavior across heterogeneous compute environments (CPU, GPU, AI accelerators). The architect will engage with internal teams and external partners (including memory and silicon vendors) to translate low-level technical characteristics into system-level guidance and platform strategy for HP. Key Responsibilities Platform Performance & Memory Analysis Analyze how AI workloads interact with system resources across CPU, GPU, and AI accelerators Evaluate the impact of memory bandwidth, latency, contention, and data movement on workload performance, responsiveness, and power efficiency Characterize workload behavior in shared-memory systems, including interactions between foreground and background activity Identify sources of performance variability and experience degradation under real-world multitasking scenarios. Overcome the performance bottleneck where processor speeds outpace memory bandwidth, focusing on optimizing data movement between CPUs, GPUs, and memory (DRAM, HBM, CXL). System-Level Guidance & Strategy Translate memory and system-level constraints into actionable guidance for platform architecture, runtime, power, and performance teams Help define execution envelopes and tradeoffs (e.g., placement, concurrency limits, configuration sensitivity) that improve AI experience predictability Contribute to platform-level strategy by connecting technical constraints to user experience outcomes and product decisions Cross-Functional & Ecosystem Collaboration Work closely with platform architecture, runtime, power/thermal, and AI enablement teams within HP Engage with external ecosystem partners, including memory and silicon vendors, to: Understand platform capabilities, tradeoffs, and roadmap directions Evaluate how memory technologies and configurations affect real-world AI experiences Translate partner insights into HP-specific system guidance and strategic recommendations Support technical alignment discussions Platform Enablement Assist in defining internal tools, metrics, and evaluation methods for assessing AI workload behavior and memory sensitivity Contribute to documentation, best practices, and internal frameworks related to system-level AI performance Help scale AI experiences across a diverse portfolio of devices and SKUs Qualifications Education: M.Sc. in Computer Engineering, Electrical Engineering, or a related discipline. Strong background in systems performance, platform architecture, or runtime behavior Solid understanding of memory hierarchy and data movement in client or embedded systems (e.g., DRAM, caches, shared memory architectures). Strong knowledge of computer architecture, specifically memory hierarchy (DRAM, SRAM, cache), interconnect protocols (CXL, PCIe), and memory controllers. Experience with Machine Learning hardware acceleration and processing-in-memory (PIM) techniques. Knowledge of low-power design, given the "power wall" constraint. Experience working with heterogeneous compute environments (CPU, GPU, accelerators) Ability to translate low-level technical constraints into system-level guidance and platform strategy Experience collaborating across hardware, software, and product organizations Strong technical communication skills, including engagement with external partners Preferred Experience Client platforms (PC, mobile, embedded) rather than exclusively datacenter or HPC environments On-device AI inference workloads Power- and performance-sensitive system design Performance analysis tools, telemetry, and data-driven evaluation Prior experience engaging with memory or silicon vendors in a technical or architectural capacity Programming: Proficiency in C/C++ and scripting languages (Python) for modeling and analysis. Simulation Tools: Experience with architectural simulators (e.g., GEM5, Sniper) and performance analysis. Salary The pay range for this role is $147,050 to $230,850 USD annually with additional opportunities for pay in the form of bonus and/or equity (applies to United States of America candidates only). Pay varies by work location, job-related knowledge, skills, and experience. Benefits: HP offers a comprehensive benefits package for this position, including: Health insurance Dental insurance Vision insurance Long term/short term disability insurance Employee assistance program Flexible spending account Life insurance Generous time off policies, including; 4-12 weeks fully paid parental leave based on tenure 11 paid holidays Additional flexible paid vacation and sick leave (US benefits overview) The compensation and benefits information is accurate as of the date of this posting. The Company reserves the right to modify this information at any time, with or without notice, subject to applicable law. Job - Engineering Schedule - Full time Shift - No shift premium (United States of America) Travel - Relocation - Equal Opportunity Employer (EEO) - HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s). Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. This information is provided voluntarily. The information obtained will be kept in strict confidence. For more information, review HP's EEO Policy or read about your rights as an applicant under the law here: "Know Your Rights: Workplace Discrimination is Illegal"
Created: 2026-03-04