Applied AI Engineer

Amd

Confirmed live 2 days ago High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Santa Clara, CA
Salary
$204,000–$306,000 / yr
Posted
43 days ago
Freshness
Confirmed live 2 days ago
Closes
Jul 30, 2027

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $191k
This role $255k
$132k most similar roles pay here $325k

This role pays more than 92% of similar roles. Most pay $153,043–$227,975 — the shaded band above. At the midpoint, this role pays about $255k versus about $191k 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 367 open roles on FindRole.

Listed pay typically runs $166,400–$249,600 across 367 roles with salary data.

Most-posted roles

View all roles at Amd

At a glance

TL;DR · Applied AI Engineer

As an Applied AI Engineer, you will join a team focused on high-priority AI-for-engineering efforts to transform complex hardware and software workflows into AI-assisted systems. You will build tools and agent loops that automate tasks such as design optimization, verification, simulation, firmware development, performance debugging, and routing. Your daily work involves converting manual processes into structured tasks with candidate generation, validation, and scoring while collaborating with domain experts to define success metrics like correctness and latency. The role requires proficiency in Python and systems languages including C++, C, HIP, CUDA, or Rust. You will develop agentic systems for code generation and root-cause analysis using compilers, simulators, and profilers. This position addresses the technical challenge of integrating LLMs into hardware-adjacent domains to improve engineering efficiency through automated validation and reproducible workflows.

What you'll do

  • Build applied AI workflows for hardware and software engineering priorities like optimization, verification, and debugging.
  • Convert manual engineering processes into structured tasks with automated candidate generation, validation, and scoring.
  • Develop tools that enable AI agents to interact with compilers, simulators, profilers, and ticket systems.
  • Create human-in-the-loop workflows for tasks requiring expert judgment or subjective triage.
  • Improve model and agent performance through prompt engineering, retrieval, evaluation datasets, and structured feedback.
  • Collaborate with domain experts to define success metrics such as correctness, latency, and time saved.
  • Generalize repeated patterns into reusable platforms, dashboards, and data assets with research and infrastructure teams.
  • Communicate project progress through measurable outcomes, technical writeups, and stakeholder updates.

What we're looking for

  • Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, Machine Learning, or a related field.
  • Master's degree preferred; PhD is a plus for candidates with relevant AI, systems, EDA, or hardware/software co-design experience.
  • Strong software engineering experience in Python and at least one systems language such as C++, C, HIP, CUDA, or Rust.
  • Experience building applied AI, ML, agentic, automation, or developer tooling systems for technical users.
  • Experience with hardware design or verification workflows including RTL, Verilog/SystemVerilog, simulation, formal verification, and EDA tools.
  • Experience with GPU/CPU performance engineering, compiler tooling, profilers, kernel optimization, ROCm/HIP, CUDA, or benchmarking.
  • Familiarity with LLM agents, tool use, retrieval, LLM-as-judge workflows, RL, or post-training methods.
  • Experience designing evaluation datasets, graders, dashboards, leaderboards, or experiment tracking systems.

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