Spring/Summer 2027 PhD Large Language Model Engineer Co-op

AMD

Posted 28 days ago

San Jose, California

Hybrid

Smart Summary

Responsibilities

The intern will conduct research on scalable training and inference for large language models while developing distributed training frameworks and optimization strategies. They will collaborate with engineering teams to implement hardware-aware optimizations and publish findings in top-tier research conferences.

Qualifications

You are a PhD student in Computer Science, Electrical Engineering, or a related field with a focus on ML Systems, HPC, or AI Infrastructure. You have a strong background in machine learning, distributed systems, and parallel computing, with experience in deep learning frameworks and large-scale model training.

Must Have Skills for ATS

PyTorch

TensorFlow

JAX

Python

C++

GPUs

ASICs

MPI

Rcom/CUDA

RCCL/NCCL

Triton

XLA

MLIR

Job Description



ADVANCE YOUR CAREER. ADVANCE THE WORLD. 

At AMD, we believe technology has the power to solve the world’s most important challenges. From advancing healthcare and scientific discovery to powering AI and the technologies people rely on every day, innovation at AMD is shaping the future. 

Whether you’re designing next-gen processors, enabling AI breakthroughs, or bringing leading edge products to market, every role at AMD contributes to something bigger — technology that moves the world forward. Join us and, together, we’ll advance your career.




As an AMD co-op, you’ll be placed at the epicenter of the AI ecosystem, working alongside experts and industry pioneers. You’ll do important work, learn new skills, expand your network, and gain real-world experience on projects that impact millions of end-users worldwide. Whether you’re an undergrad or a PhD student, your contributions matter—and your experience here will be a launchpad for what comes next.

JOB DETAILS:

  • Location: San Jose, CA, USA
  • Onsite: This role requires the student to work full time (40 hours a week), onsite work structure throughout the duration of the co-op/intern term. 
  • Duration: Spring/Summer 2027 Co-Op: January 25, 2027 - August 13, 2027

WHAT YOU WILL BE DOING:

We are seeking a highly motivated LLM Research Intern pursuing a PhD in Machine Learning (ML) Systems, High-Performance Computing (HPC), or related fields. This internship offers an opportunity to contribute to cutting-edge research at the intersection of large language models (LLMs), distributed computing, and system optimization. The selected intern will work closely with our research and engineering teams to explore innovative techniques to enhance the efficiency, scalability, and performance of LLM training and inference on modern hardware architectures.  

  • Conduct research on scalable training and inference of large language models, focusing on ML systems and HPC techniques
  • Develop and optimize distributed training frameworks, model parallelism strategies, and efficient resource management for large-scale AI workloads.
  • Explore hardware-aware optimizations, including algorithm-hardware co-optimization, sparsity-aware computation, quantization, and memory-efficient techniques for LLMs.
  • Implement and benchmark state-of-the-art ML system optimizations, leveraging high-performance computing techniques.
  • Collaborate with researchers and engineers to publish findings in top-tier conferences (NeurIPS, ICML, MLSys, SC, etc.). 

WHO WE ARE LOOKING FOR:

  • Currently pursuing a PhD in Computer Science, Electrical Engineering, or a related field with a focus on ML Systems, HPC, or AI Infrastructure.
  • Strong background in machine learning, distributed systems, and parallel computing.
  • Experience with deep learning frameworks (e.g., PyTorch, TensorFlow, JAX) and large-scale model training.
  • Proficiency in Python and C++, with experience in performance profiling and optimization.
  • Knowledge of GPUs, ASICs, distributed training paradigms (e.g., data/model pipeline parallelism, FSDP, ZeRO, DeepSpeed, Megatron-LM).
  • Familiarity with HPC techniques, including MPI, Rcom/CUDA, RCCL/NCCL, and high-speed networking technologies.
  • Prior research experience in scalable deep learning systems, large-scale LLM training, or AI acceleration.
  • Experience with AI compiler optimizations (e.g., Triton, XLA, MLIR)

Note: By submitting your application, you are indicating your interest in AMD intern positions. We are recruiting for multiple positions, and if your experience aligns with any of our intern opportunities, a recruiter will contact you.

This role is not eligible for visa sponsorship.




Benefits offered are described:  AMD benefits at a glance.

AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law.   We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process.

AMD may use Artificial Intelligence to help screen, assess or select applicants for this position.  AMD’s “Responsible AI Policy” is available here.

This posting is for an existing vacancy.

AMD

We care deeply about transforming lives with AMD technology to enrich our industry, our communities, and the world. Our mission is to build great products that accelerate next-generation computing experiences – the building blocks for the data center, artificial intelligence, PCs, gaming and embedded. Underpinning our mission is the AMD culture. We push the limits of innovation to solve the world’s most important challenges. We strive for execution excellence while being direct, humble, collaborative, and inclusive of diverse perspectives. AMD together we advance_
Runway Icon
Boost Your Interview Chances

With Runway

See Your Fit for This Role

1-5 min

Your Score

?

Top Applicants

90%

Your Job Search Advantage

Key Gaps & Next Steps:

Address these in your resume & Interview

Top Strengths For This Role

Highlight these in your cover letter & interview

Your Interview Guide

A Personalized Interview Strategy

Freshest Opportunities

Never Miss a Good Fit

Get notified when jobs mach your criteria