GPU Chief Architect / XPU Lab Director

Job Summary

We are seeking a highly experienced GPU architect to lead the definition and execution of next generation mobile GPU architecture in our Kirin SOC, driving architectural convergence between GPU and NPU toward a coherent xPU sub system design.

This role requires deep expertise in GPU microarchitecture, strong system level architectural capability including hardware and software, and a thorough understanding of graphics and AI common workloads. A proven track record of delivering related sub system IP or complex SoC silicon is highly desirable.

The successful candidate will shape a converged xPU architecture native for future AI compute, optimized for performance, power efficiency, and silicon area in next generation mobile compute platforms.

Key Responsibilities

• Analyze and characterize future mobile graphics and AI workloads, redefine an xPU (GPU & NPU) converged architecture, including hardware and software, from the ground up that is optimal for future applications.
• Ensure compatibility or easy transition from the old architecture.
• Define unified or partially unified execution resources (vector, scalar, tensor units).
• Develop shared scheduling and workload dispatch mechanisms for graphics and AI.
• Design resource sharing and isolation strategies under mixed workloads.
• Evaluate architectural trade offs between dedicated and converged compute blocks.
• Mobile GPU Architecture Leadership
• Ensure the timely delivery of next generation mobile GPU architecture and long term roadmap.
• Lead evolution of shader cores, execution pipelines, and cache hierarchy.
• Drive performance, power efficiency (Perf/W), and area efficiency (Perf/mm ).
• Provide architectural leadership from concept phase through tape out.
• Memory & Interconnect Architecture
• Define a memory hierarchy strategy for converged GPU/NPU workloads.
• The architect shared cache structures and bandwidth arbitration policies.
• Optimise on chip interconnect for heterogeneous compute traffic.
• Reduce data movement overhead across compute domains.
• System Level Architecture Collaboration
• Collaborate with CPU, AI software, runtime, and system architecture teams.
• Participate in SoC level power, thermal, and floorplanning trade offs.
• Align hardware architecture with graphics APIs and AI frameworks.
• Support performance modelling, workload characterisation, and silicon bring up.

Required

• 15+ years of experience in GPU, AI accelerator, or heterogeneous compute architecture.
• Deep understanding of GPU microarchitecture (SIMD/SIMT, scheduling, memory systems).
• Strong knowledge of tensor/matrix computation and AI acceleration techniques.
• Proven experience delivering high volume silicon.
• Expertise in performance modelling and power analysis.
• Strong cross functional communication and leadership capability.

What we offer

• 33 days annual leave entitlement per year (including UK public holidays).
• Group Personal Pension.
• Life insurance.
• Private medical insurance.
• Medical expense claim scheme.
• Employee Assistance Program.
• Cycle to work scheme.
• Company sports club and social events.
• Additional time off for learning and development.