GPU Modeling / GPU Architect (Senior/Principal Engineer)

PER International; California (MO); On-site; USD 170,000 - 260,000; Full time

Job summary

PER International is seeking a Senior/Principal Engineer to define and develop next‑generation GPU architectures for SoCs in a highly technical, individual‑contributor role. You will build models, simulate performance and power, and guide architectural trade‑offs across RTL, DV, software and performance teams.

You will analyze workloads from games to AI kernels, drive optimization opportunities, and influence roadmap decisions for future GPU products with a focus on efficiency and scalability.

Qualifications

• BS/MS or higher in Computer Science, Electrical/Computer Engineering or a closely related field.
• 8+ years of experience in GPU, graphics, high‑performance compute, AI accelerator, or related architecture/modeling areas.
• Deep understanding of modern GPU architecture and pipeline (graphics and/or compute).
• Strong experience with performance and/or cycle‑accurate modeling, simulation frameworks, or architectural exploration for complex SoCs or accelerators.
• Solid understanding of graphics and compute APIs such as Vulkan, OpenGL, DirectX and/or GPU compute frameworks (e.g., OpenCL, CUDA, Metal).
• Proficiency in at least one modeling or implementation language (e.g., C/C++, SystemC, Python).
• Experience with performance analysis tools, profiling methodologies and workload characterization.

Responsibilities

• Define and develop best‑in‑class GPU architecture and performance/power models for next‑generation SoCs.
• Build and maintain cycle‑accurate / performance / functional models of GPU subsystems (shader cores, fixed‑function units, memory hierarchy, interconnect).
• Use modeling and profiling to explore architectural trade‑offs (performance, power, area) and guide micro‑architecture decisions.
• Analyze workloads (games, graphics benchmarks, GPU compute, AI/ML kernels) using simulation and hardware profiling to identify bottlenecks and optimization opportunities.
• Collaborate with RTL, DV, software/driver, and performance teams to ensure architectural intent is implemented, verified and tuned.
• Provide architectural input to compiler/driver/runtime teams to maximize GPU hardware utilization through software optimizations.
• Develop methodologies, tools and automation flows for GPU performance estimation, capacity planning and regression analysis.
• Lead debug and root‑cause analysis of performance, power and bandwidth issues observed in models, emulation and silicon.
• Drive cross‑team technical discussions, present modeling results and architectural proposals, and influence roadmap decisions.

Skills

GPU architecture

Modeling and simulation

Performance analysis

Cross-functional collaboration

C/C++ programming

SystemC

Python scripting

CUDA/OpenGL/Vulkan

Education

Bachelor’s or Master’s in Computer Science or Electrical/Computer Engineering

Tools

CUDA

OpenGL

Vulkan

DirectX

Job description

Position: GPU Modeling / GPU Architect (Senior/Principal Engineer)

Location: San Diego or San Jose (4 days onsite)

Employment Type: Full-Time

**Overview**

We are seeking a GPU Modeling/GPU Architect (Senior/Principal Engineer) to help define and develop next-generation GPU architectures for advanced SoC platforms. In this role, you will be responsible for building and driving industry‑leading GPU performance and power models, enabling architectural exploration, workload analysis, and data‑driven design decisions. You will collaborate closely with architecture, RTL, verification, software, and performance teams to shape future GPU products and maximize performance, efficiency, and scalability.

This is a highly technical individual contributor role that offers the opportunity to influence next‑generation GPU architecture through modeling, simulation, performance analysis, and cross‑functional leadership.

**Role and Responsibilities**

• Define and develop best‑in‑class GPU architecture and performance/power models for next‑generation SoCs.
• Build and maintain cycle‑accurate / performance / functional models of GPU subsystems (e.g., shader cores, fixed‑function units, memory hierarchy, interconnect).
• Use modeling and profiling to explore architectural trade‑offs (performance, power, area) and guide micro‑architecture decisions.
• Analyze workloads (games, graphics benchmarks, GPU compute, AI/ML kernels) using simulation and hardware profiling to identify bottlenecks and optimization opportunities.
• Collaborate closely with RTL, DV, software/driver, and performance teams to ensure architectural intent is correctly implemented, verified and tuned.
• Provide architectural input to compiler/driver/runtime teams to maximize utilization of GPU hardware through software optimizations.
• Develop methodologies, tools and automation flows for GPU performance estimation, capacity planning and regression analysis.
• Lead the debug and root‑cause analysis of performance, power and bandwidth issues observed in models, emulation and silicon.
• Drive cross‑team technical discussions, present modeling results and architectural proposals, and influence roadmap decisions for next‑generation GPUs.

**Required Skills & Experience**

• BS/MS or higher in Computer Science, Electrical/Computer Engineering or a closely related field.
• 8+ years of experience in GPU, graphics, high‑performance compute, AI accelerator, or related architecture/modeling areas.
• Deep understanding of modern GPU architecture and pipeline (graphics and/or compute), including shader cores, rasterization, tiling, memory systems and scheduling.
• Strong experience with performance and/or cycle‑accurate modeling, simulation frameworks, or architectural exploration for complex SoCs or accelerators.
• Solid understanding of graphics and compute APIs such as Vulkan, OpenGL, DirectX and/or GPU compute frameworks (e.g., OpenCL, CUDA, Metal).
• Proficiency in at least one modeling or implementation language (e.g., C/C++, SystemC, Python) and familiarity with scripting for data analysis and automation.
• Experience with performance analysis tools, profiling methodologies and workload characterization for games, benchmarks and/or GPU compute workloads.
• Good written and oral communication skills, with the ability to present complex technical topics clearly and drive consensus across teams.

**Preferred Skills**

• Experience with mobile/low‑power GPU design and power/performance trade‑off analysis.
• Background in compiler, driver, or runtime optimization for GPUs or accelerators.
• Familiarity with ML/AI workloads, DNN operators and their mapping onto GPU or accelerator architectures.
• Experience collaborating with silicon implementation, physical design and DV teams on performance and power sign‑off.