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# Senior AI Performance Modeling Architect

- **Company:** Advanced Micro Devices, Inc.
- **Location:** Austin, TX, United States
- **Experience:** Expert
- **Salary:** $174,400.0
- **Contract:** Permanent contract
- **Skills:** Adobe Flash, Artificial Intelligence, Profiling, Nvidia CUDA, Distributed Systems, InfiniBand, Performance Tuning, Remote Direct Memory Access, OpenAI, Software Engineering, AI Infrastructure, Graphics Processing Unit (GPU), Pytorch, Large Language Models, Discretization, Attention Mechanisms, Information Technology, Transformer Architectures, Machine Learning Operations, TensorRT, Megatron, GPT, Deepseek (AI Talent Sourcing Platform)
- **Published:** October 15, 2026
- **Apply:** https://diversityjobs.com/career/18639037/Senior-Ai-Performance-Modeling-Architect-Texas-Austin

## About the Role

You have a deep understanding of GPU microarchitecture, memory hierarchies, and their impact on large-scale ML workloadsYou are passionate about software engineering and possess leadership skills to drive sophisticated issues to resolution. You are able to communicate effectively and work optimally with different teams across AMD., * Extensive and Senior experience optimizing large-scale ML systems and GPU architectures

 * Deep expertise in CUDA programming, GPU memory hierarchies, and hardware-specific optimizations
 * Proven track record architecting distributed training systems handling large scale systems
 * Expert knowledge of transformer architectures, attention mechanisms, and model parallelism techniques

PREFERRED EXPERIENCE:

 * PyTorch, CUDA, TensorRT, OpenAI Triton
 * Distributed systems: Ray, Megatron-LM
 * Performance analysis tools: NSight Compute, nvprof, PyTorch Profiler
 * KV cache optimization, Flash Attention, Mixture of Experts
 * High-speed networking: InfiniBand, RDMA, NVLink

ACADEMIC CREDENTIALS:

 * Bachelors, MS/PhD in Computer Science/Engineering or equivalent industry experience

## Description

As a Senior Engineer, you will lead engineers with the next generation of AI infrastructure by defining GPU architecture specifications that enable massive model training at scale. Your expertise will drive 2-3x performance gains in both training and inference pipelines through innovative system design and optimization. You will champion the adoption of cutting-edge techniques across the engineering organization, from efficient attention mechanisms to advanced parallelization strategies. By establishing comprehensive best practices for distributed ML systems, you will create a framework that enables seamless scaling from single-GPU to thousand-GPU deployments., * Lead performance modeling and optimization for multi-trillion parameter LLM training/inference including Dense, Mixture of Experts (MoE) with multiple modalities (text, vision, speech)

 * Model/optimize novel parallelization strategies across tensor, pipeline, context, expert and data parallel dimensions
 * Architect memory-efficient training systems utilizing techniques likestructured pruning, quantization (MX formats), continuous batching/chunked prefill, speculative decoding
 * Incorporate and extend SOTA models such as GPT-4, Reasoning models (Deepseek-R1), and multi-modal architectures
 * Collaborate with internal and external stakeholders/ML researchers to disseminate results and iterate at rapid pace., AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD's "Responsible AI Policy" is available here.