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.
Qualifications
Required Qualifications
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.
Good-to-Have Skills
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.
We're looking for talented individuals excited to solve complex challenges and shape the future of platform architecture. If you're ready to make an impact and contribute to Intel's success, we encourage you to apply today.
Job Type
Experienced Hire
Shift
Shift 1 (India)
Primary Location
India, Bangalore
Additional Locations
Posting Statement
All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.
- Work Model for this Role
- This role will be eligible for our hybrid work model which allows employees to split their time between working on-site at their assigned Intel site and off-site. * Job posting details (such as work model, location or time type) are subject to change.
ADDITIONAL INFORMATION: Intel is committed to Responsible Business Alliance (RBA) compliance and ethical hiring practices. We do not charge any fees during our hiring process. Candidates should never be required to pay recruitment fees, medical examination fees, or any other charges as a condition of employment. If you are asked to pay any fees during our hiring process, please report this immediately to your recruiter.
