GPU Architecture and AI Performance Simulation Engineer
Intel · Posted Oct 26
Semiconductor manufacturing, microprocessors, data center solutions, and artificial intelligence infrastructure
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About the role
The role sits within Intel's platform architecture organization, focused on analyzing, modeling, and optimizing AI workload performance on GPU and SoC architectures to shape architectural decisions across current and future silicon. Work spans AI workloads built on Transformer and Mixture-of-Experts architectures, multi-GPU and at-scale AI systems, and roofline and cycle-accurate performance models. This engineer will guide the team in fine-tuning workload, SoC, and system models, propose data-backed architectural enhancements, and track the AI GPU market to inform Intel's future accelerator roadmap.
What you will do
- Analyze AI workload behavior on GPU architectures - distinguishing compute-bound, memory-bound, and cache-bound behavior to identify performance bottlenecks and optimization opportunities.
- Build and maintain roofline analytical models and cycle-accurate performance models to support hardware what-if studies and guide micro-architectural decisions.
- Analyze AI workloads built on Transformer and Mixture-of-Experts (MoE) architectures, inference and training, and assess the hardware-utilization impact of kernel-level optimizations such as Flash Attention, Flash Decode, Sparse Attention, and Causal Masking.
- Model and analyze multi-GPU and at-scale AI systems - workload distribution, synchronization overhead, and communication-compute overlap.
- Drive workload and architectural bottleneck analysis for the early architecture definition phases of Intel's future AI GPU accelerator roadmap products.
- Guide and mentor the team in delivering analytical models and end-to-end system-level performance projections; review modeling methodology and drive consistency across studies.
- Propose new architectural enhancement ideas, backed by quantitative modeling data and workload evidence.
- Maintain a forward-looking view of the AI GPU and accelerator market - tracking competitive roadmaps, whitepapers, and conferences - and translate those trends into architectural requirements while keeping the team updated on applicable AI innovations.
Skills used in this role
What the employer is looking for
- Bachelor's with 10+ yrs, master's with 8+ years and Ph.D with 5+ years of experience in System/GPU/SoC performance engineering, AI workload analysis, or hardware architecture.
- Deep knowledge of GPU microarchitecture (NVIDIA SM/CUDA cores, Intel Xe cores, or equivalent), GPU execution pipelines, and cache hierarchy design (L1/L2/L3).
- Familiarity with SoC design principles, on-chip fabric, memory subsystems, and interconnects.
- Experience with multi-GPU system architectures (NVLink, PCIe, CXL, or equivalent) and scaling AI workloads across multiple devices.
- Good understanding of distributed training/inference techniques: Tensor Parallel, Data Parallel, Pipeline Parallel, Expert Parallel, and Model Split methodologies.
Preferred qualifications
- Experience with cycle-accurate simulators or hardware performance emulation platforms.
- Familiarity with AI framework internals (PyTorch, JAX, TensorFlow) and kernel-level optimization (CUDA, SYCL, HIP, Triton).
- Exposure to LLM inference optimization techniques (quantization, KV-cache management, speculative decoding).
- Experience with performance profiling tools (e.g., NVIDIA Nsight, Intel VTune, AMD ROCProfiler, or similar).
- Publications or patents in GPU architecture, AI systems performance, or related areas.
Benefits and support
- Compensation and benefits are detailed in the job posting
About Intel
Intel Corporation is a global technology leader focused on the design and manufacturing of microprocessors, integrated circuits, and advanced data center infrastructure. The company drives innovation across personal computing, artificial intelligence, and cloud ecosystems while operating a major semiconductor foundry business. Intel delivers foundational silicon and packaging solutions that power modern digital infrastructure worldwide.
- Industry
- Semiconductors
- Company size
- 10001+ employees
- Founded
- 1968
- Location
- Santa Clara, California, USA
- Funding stage
- Public Company
Leadership
Lip-Bu Tan
Chief Executive Officer
Executive Vice President and Chief Financial Officer
Pushkar Ranade
Chief Technology Officer and Chief of Staff to the CEO
Executive Vice President – Chief Technology and Operations Officer, General Manager Intel Foundry
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