PhD Applied AI Engineering Intern, Hardware AI

Amd

Confirmed live today High trust

Hybrid

Quick summary

Work type: Hybrid
Location: Santa Clara, CA
Salary: $91,520–$137,280 / yr
Employment: Intern
Posted: 8 days ago
Freshness: Confirmed live today
Closes: Sep 23, 2027
Nearby: 99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $166k

This role $114k

$76k most similar roles pay here $234k

This role pays less than 74% of similar roles. Most pay $114,400–$218,281 — the shaded band above. At the midpoint, this role pays about $114k versus about $166k 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.

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At a glance

TL;DR · PhD Applied AI Engineering Intern, Hardware AI

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The Summer 2027 PhD Applied AI Engineering Intern, Hardware AI joins the team to build and evaluate AI-assisted workflows specifically for hardware and software engineering applications. The intern will develop tools integrating LLMs and AI agents with critical systems such as compilers, simulators, profilers, and validation frameworks. Key responsibilities include automating engineering workflows through candidate generation and evaluation, improving prompt engineering and retrieval systems, and defining metrics for correctness and productivity. The role requires proficiency in Python and experience with PyTorch or similar machine learning frameworks. Candidates must have a background in artificial intelligence or computer systems to address the technical challenge of enhancing engineering productivity. This position focuses on the intersection of AI-assisted software development and hardware engineering workflows, requiring the analysis of performance data to improve reliability and automation within complex engineering environments.

Skills

Python LLMs AI Agents PyTorch Machine Learning Retrieval Systems Compiler Simulators Profilers Validation Frameworks Benchmarking Experiment Tracking Automation Computer Systems

What you'll do

Build and evaluate AI-assisted workflows for hardware and software engineering applications.
Develop tools integrating LLMs and AI agents with compilers, simulators, profilers, and validation frameworks.
Automate engineering workflows through candidate generation, validation, evaluation, and structured feedback.
Define metrics for correctness, performance, and engineering productivity alongside researchers and engineers.
Contribute to evaluation datasets, benchmarking, and experiment tracking for AI-assisted workflows.
Improve prompts, retrieval systems, and tool interfaces to enhance AI agent performance.
Analyze workflow performance to identify opportunities for improved reliability, efficiency, and automation.
Document technical designs, experimental results, and implementation details.

What we're looking for

Must be currently enrolled in a PhD program in Computer Science, Computer Engineering, Electrical Engineering, Artificial Intelligence, or a related field.
Experience with Python programming.
Coursework or hands-on experience in artificial intelligence or computer systems.
Familiarity with PyTorch or similar machine learning frameworks.
Interest and familiarity in AI-assisted software development, LLMs, AI agents, or engineering productivity tools (preferred).

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