Principal Competitive CPU Microarchitecture & Platform Performance Engineer

Amd

Confirmed live today High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Austin, TX
Salary
$200,000–$300,000 / yr
Posted
1 day ago
Freshness
Confirmed live today
Closes
Sep 18, 2027

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $212k
This role $250k
$148k most similar roles pay here $316k

This role pays more than 77% of similar roles. Most pay $177,300–$246,200 — the shaded band above. At the midpoint, this role pays about $250k versus about $212k 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 391 open roles on FindRole.

Listed pay typically runs $164,080–$246,120 across 391 roles with salary data.

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At a glance

TL;DR · Principal Competitive CPU Microarchitecture & Platform Performance Engineer

The Principal Competitive CPU Microarchitecture & Platform Performance Engineer joins the Competitive Advanced Performance team to predict and validate competitive server CPU performance before products reach the market. This role involves building workload-relevant models of future AMD and competitor platforms by converting public disclosures, measured behavior, and platform observations into explicit architectural assumptions. You will develop comparative models for CPU front ends, execution resources, cache hierarchies, memory subsystems, and multi-socket behaviors while modeling constraints like memory bandwidth, PCIe, CXL, and power limits. Key responsibilities include performing bottleneck decomposition, creating microbenchmarks with workload engineers, and quantifying performance-per-watt implications. Required expertise includes deep knowledge of out-of-order pipelines, branch prediction, hardware performance counters, and system telemetry. You will use scripting and data analysis to translate incomplete roadmap information into technical narratives for both experts and decision-makers.

What you'll do

  • Build workload-relevant models of future AMD and competitor server platforms before silicon becomes available.
  • Translate incomplete roadmap disclosures into explicit assumptions with defined confidence levels and sensitivity ranges.
  • Develop comparative models for CPU front ends, execution resources, cache hierarchies, and memory subsystems.
  • Model platform constraints including memory bandwidth, PCIe, CXL, networking, power limits, and thermals.
  • Use performance counters and telemetry to calibrate models and identify failing assumptions.
  • Perform bottleneck decomposition to explain why specific architectural mechanisms favor one platform over another.
  • Collaborate with workload engineers to create microbenchmarks that isolate high-value architectural effects.
  • Create technical narratives and executive-ready content to communicate risks and areas of competitive advantage.

What we're looking for

  • Bachelor's or Master's degree in electrical or computer engineering.
  • Deep hands-on experience in CPU microarchitecture, silicon performance, system architecture, or performance modeling.
  • Strong knowledge of out-of-order pipelines, branch prediction, fetch and decode, execution back ends, and simultaneous multithreading behavior.
  • Expertise in cache, TLB, coherence, prefetching, memory controllers, NUMA, bandwidth, latency, and capacity scaling.
  • Experience with hardware performance counters, profiling tools, microbenchmarks, system telemetry, and bottleneck analysis.
  • Strong quantitative skills combined with scripting or data-analysis skills for performance investigations.
  • Clear technical writing and visualization skills to communicate complex results to both experts and decision-makers.
  • Pre-silicon modeling, multi-architecture analysis, and experience with memory-intensive workloads or AI workloads (preferred).

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