PhD HPC & Sovereign AI Center of Excellence Intern/Co-op

Amd

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Quick summary

Work type
On-site
Location
Austin, TX
Salary
$91,520–$137,280 / yr
Employment
Intern
Posted
20 days ago
Freshness
Confirmed live today
Closes
Sep 21, 2027
Nearby
99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $175k
This role $114k
$74k $253k
below market most similar roles pay here above market

This role pays less than 73% of similar roles. Most pay $114,400–$235,750 — the blue band above. At the midpoint, this role pays about $114k versus about $175k 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 510 open roles on FindRole.

Listed pay typically runs $172,000–$258,000 across 510 roles with salary data.

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At a glance

TL;DR · PhD HPC & Sovereign AI Center of Excellence Intern/Co-op

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JOB TITLE: 2027 PhD HPC & Sovereign AI Center of Excellence Intern/Co-op As a PhD intern, you will join the research team at the intersection of High-Performance Computing and Artificial Intelligence. You will contribute to projects optimizing AI workloads for large-scale computing environments, developing novel algorithms, and exploring AI techniques to enhance HPC applications. Your daily responsibilities include building and analyzing performance benchmarks on GPU accelerated platforms, assessing development tools and runtime environments, and exploring code optimization techniques. You will specifically work on optimizing communication patterns, investigating GPU tool adaptations, and porting synthetic workloads to adaptiveCPP (SYCL). Required skills include proficiency in Python, C/C++, Fortran, ROCm/CUDA, and deep learning frameworks like PyTorch, TensorFlow, or JAX. You must possess a background in parallel computing, distributed systems, MPI, OpenMP, and GPU kernel development.

Skills

High-Performance Computing Artificial Intelligence Python C/C++ Fortran PyTorch TensorFlow JAX ROCm CUDA MPI OpenMP SYCL GPU Programming Distributed Systems Parallel Computing Numerical Methods Performance Analysis Jira

What you'll do

  • Build, run, and analyze the performance of benchmarks and applications on GPU accelerated platforms.
  • Assess the capabilities, performance, and usability of development tools and runtime environments.
  • Explore and evaluate the benefits of various code optimization techniques.
  • Optimize communication patterns for High-Performance Computing (HPC) applications.
  • Investigate how GPU development tools can be adapted for future AMD GPUs.
  • Identify and measure performance capabilities across different GPU families.
  • Use LLM workflows and internal AI tools to incorporate existing bug reproducers.
  • Port synthetic workloads to adaptiveCPP (SYCL) and measure resulting performance.

What we're looking for

  • Currently enrolled in a PhD program in Computer Science, Computational Science, Electrical/Computer Engineering, Applied Mathematics, or a related field.
  • Strong background in parallel computing, distributed systems, or AI/ML frameworks.
  • Proficiency in programming languages such as Python, C/C++, Fortran, or ROCm/CUDA.
  • Experience with at least one deep learning framework such as PyTorch, TensorFlow, or JAX.
  • Familiarity with MPI, OpenMP, or GPU programming.
  • Solid understanding of numerical methods, optimization, or scientific computing.
  • Experience with performance analysis and hot-spot identification.
  • Experience developing GPU kernels and analyzing the benefits of GPU offloading.

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