This role pays more than
97%
of similar roles. Most pay
$205,437–$272,162
— the shaded band above.
At the midpoint, this role pays about
$348k
versus about
$239k
for comparable roles.
Based on 240 similar postings.
Employer
About Amd
AMD (Advanced Micro Devices) is a semiconductor company that develops high-performance processors, graphics cards, and adaptive computing solutions for gaming, data centers, and embedded markets. Industry: Semiconductors
Amd currently has
474 open roles
on FindRole.
Listed pay typically runs
$166,400–$249,600
across 474 roles with salary data.
Sr Director, Silicon Performance and Design Execution leads a global organization of engineers focused on end-to-end silicon performance and design execution across post-silicon phases. This role provides technical and organizational leadership for system-level performance attainment, hardware and software optimizations, silicon debug, and sustained performance delivery for complex SoCs and accelerators. The position involves driving cross-functional alignment to meet power and efficiency targets while managing AI workloads including LLMs, LDMs, and ranking engines. Key responsibilities include workload characterization, simulation, root-cause analysis, and system profiling for rack scale and AI clusters. Required expertise includes performance modeling, benchmarking, and architecture evaluation for Data Center GPUs. Technical proficiency is required in PyTorch, vLLM, SGLang, JAX, TensorFlow, Transformer Engine, and ONNX to optimize software frameworks and parallelization techniques across GPU-accelerated systems.
Own end-to-end silicon performance and design execution across all post-silicon phases.
Lead technical and organizational efforts for system-level performance, hardware/software optimizations, and silicon debug.
Drive cross-functional alignment between architecture, design, validation, software, and product teams to meet power and efficiency targets.
Manage a global organization of 30 to 50+ engineers focused on AI/ML workload performance.
Lead the characterization, simulation, and root-cause analysis for AI/ML workloads across pre-silicon and post-silicon phases.
Identify key features in DC GPUs and software frameworks for LLMs, LDMs, and ranking engines.
Provide direction for system profiling and bottleneck analysis for rack-scale systems and AI clusters.
Influence architecture features and software optimizations based on large-scale AI workload analysis.
What we're looking for
Bachelor's or Master's degree in electrical or computer engineering.
Experience managing a global organization of 30+ engineers with potential to grow to 50+.
Proven leadership in end-to-end silicon performance and design execution across post-silicon phases for complex SoCs and accelerators.
Ability to drive cross-functional alignment between architecture, design, validation, software, and product teams.
Experience in AI/ML performance engineering with hands-on experience in LLM, generative AI, and large-scale training/inference workloads (preferred).
Deep experience in Data Center GPU leading performance architecture for compute, memory, and communications for AI workloads (preferred).
Expertise in Systems Architecture and performance optimizations for AI workloads, including parallelization techniques in hardware design and software frameworks (preferred).
Knowledge of AI software components and frameworks such as PyTorch, vLLM, SGLang, JAX, TensorFlow, Transformer Engine, and ONNX (preferred).
SoC
System Architecture
Silicon Roadmap
AI
CPU
GPU
NPU
Memory
Power Management
Performance Analysis
System Modeling
Firmware
Heterogeneous Compute
Security