Systems Architect: Memory Wall Exploration

HP Development Company, L.P. • $147K — $230K *
Spring, TX 77379In-Person
Information Technology
Less than 5 years of experience
Reposted Today
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Job Overview by Ladders

Qualifications

  • M.Sc. in Computer Engineering, Electrical Engineering, or related discipline.
  • Background in systems performance, platform architecture, or runtime behavior.
  • Understanding of memory hierarchy and data movement in embedded systems.
  • Experience with Machine Learning hardware acceleration and processing-in-memory techniques.
  • Knowledge of low-power design for efficient processing.
  • Experience working with heterogeneous compute environments (CPU, GPU, accelerators).
  • Strong technical communication skills with external partners.

Responsibilities

  • Analyze AI workloads and their interaction with system resources.
  • Evaluate memory bandwidth, latency, and data movement impacts on performance.
  • Characterize behavior in shared-memory systems.
  • Identify performance variability in multitasking scenarios.
  • Translate memory constraints into actionable platform strategies.
  • Define execution envelopes to enhance AI experience predictability.
  • Collaborate with internal teams and external vendors for technical insights.

Benefits

  • Health, dental, and vision insurance
  • Long and short-term disability insurance
  • Employee assistance program
  • Flexible spending account options
  • Life insurance benefits
  • Generous parental leave policy
  • 11 paid holidays and flexible vacation options.
Full Job Description
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 -

About HP Development Company, L.P.

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Learn more about HP Development Company, L.P.
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Information Technology
* Ladders Estimates

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