Senior/Principal Engineer – GPU Modeling / GPU Architect

Job description

MediaTek Incorporated is a global fabless semiconductor company that enables nearly 2 billion connected devices a year. We are a market leader in developing innovative systems-on-chip (SoC) for mobile devices, home entertainment, connectivity and IoT products. MediaTek is the number one Wi Fi supplier across broadband, retail routers, consumer electronics devices and gaming, and its Wi Fi 6 chipsets are powering the latest networking equipment for faster computing experiences.

Our dedication to innovation has positioned us as a driving market force in several key technology areas, including highly power efficient mobile technologies, automotive solutions and a broad range of advanced multimedia products such as smartphones, tablets, digital televisions, 5G, Voice Assistant Devices (VAD) and wearables. MediaTek empowers and inspires people to expand their horizons and achieve their goals through smart technology, more easily and efficiently than ever before.

We work with the brands you know and trust to make great technology accessible to everyone.

• Define and develop best in class GPU architecture and performance/power models for next generation MediaTek 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.