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/mm²).
- 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.
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