2027 PhD AI Systems & GPU Performance Engineering Intern

AMD; San Jose (CA); Hybrid; USD 34,000 - 55,000; Full time

Job summary

AMD is seeking a PhD AI Systems & GPU Performance Engineering Intern in San Jose, CA. You will optimize AI models and training workflows on AMD Instinct GPUs, profiling with ROCm, Triton, and related tools.

You’ll develop benchmarking frameworks, analyze end‑to‑end AI workflows including LLMs, and deliver data‑driven recommendations to improve efficiency and throughput. This internship offers hands‑on work with cutting‑edge hardware and collaboration with researchers.

Qualifications

• PhD candidate with expected graduation after internship.
• Hands-on programming in Python and C/C++.
• Experience with Linux, profiling and performance analysis.

Responsibilities

• Profile, benchmark, and optimize AI training and inference workloads on AMD Instinct GPUs.
• Develop reproducible benchmarking frameworks and automation scripts.
• Analyze end-to-end AI workflows including LLMs and generative AI.
• Provide data-driven recommendations to improve efficiency, throughput, and latency.
• Collaborate with engineers and researchers on performance investigations.

Skills

Python

C/C++

Linux scripting

Profiling

Performance analysis

Education

PhD in Computer Science/Engineering/Applied Mathematics

Tools

CUDA

HIP

Triton

ROCm Profiler

ROCm

Job description

ADVANCE YOUR CAREER. ADVANCE THE WORLD.

At AMD, we believetechnology 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 AMDis shapingthefuture.

Whetheryou’redesigning next-gen processors, enabling AI breakthroughs, orbringing leading edge products to market, every role at AMD contributes to something bigger— technologythat moves the world forward.Join us and, together, we’ll advance your career.

As an AMD intern or 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 or Santa Clara,CA
• Onsite/Hybrid: This role requires the student to work full time (40 hours a week), in either a hybrid or onsite work structure throughout the duration of the co-op/intern term

• Duration:

  • Spring/Summer Co-op: January 25, 2027 - August 13, 2027
  • Summer Internship
    • Semester Students: May 24, 2027 - August 13, 2027
    • Quarter Students: June 21, 2027 - September 10, 2027
  • Summer/Fall Co-op
    • Semester Students: May 24, 2027 - December 10, 2027
    • Quarter Students: June 21, 2027 - December 10, 2027

WHAT YOU WILL BE DOING:

We are seeking a highly motivated PhD AI Systems & GPU Performance Engineering Intern to join our team. In this role, you will help optimize state-of-the-art AI models, training workflows, and inference applications on AMD Instinct™ GPUs using AMD's latest hardware and software technologies.

• We will involve you in profiling, benchmarking, and optimizing AI training and inference workloads using ROCm™, PyTorch, JAX, vLLM, Triton, and related performance engineering tools, helping identify bottlenecks across compute, memory bandwidth, communication, and kernel execution.
• Your responsibility will include developing reproducible benchmarking frameworks and automation scripts that enable performance validation across AI models, software stacks, runtimes, drivers, and accelerator platforms.
• We will train you to analyze and optimize end‑to‑end AI workflows, including large language models (LLMs) and generative AI applications, exploring techniques such as model optimization, operator fusion, scheduling strategies, mixed precision, and quantization.
• You will work closely with engineers and researchers to evaluate GPU performance, compare workload characteristics across hardware and software environments, and contribute data‑driven recommendations that improve efficiency, scalability, throughput, latency, and overall system utilization.
• You get to explore cutting‑edge AI systems research on AMD's newest hardware platforms while contributing profiling analysis, performance investigations, and optimization solutions that advance next‑generation AI training and inference technologies.

WHO WE ARE LOOKING FOR:

• Currently pursuing a PhD in Computer Science, Computer Engineering, Electrical Engineering, Applied Mathematics, or a related technical field, with an expected graduation date after the internship concludes.
• Hands‑on programming experience in Python and C/C++, with exposure to accelerator programming technologies such as CUDA, HIP, Triton, or similar frameworks.
• Experience with deep learning frameworks such as PyTorch, JAX, or TensorFlow and familiarity with large‑scale AI model training and inference concepts.
• Experience working in Linux environments, including scripting, debugging, profiling, and performance analysis.
• Exposure to GPU architecture concepts such as memory hierarchy, parallel execution, kernel optimization, communication efficiency, operator fusion, scheduling, or accelerator performance characteristics through research, coursework, or projects.
• Familiarity with profiling, benchmarking, and performance analysis methodologies using tools such as rocProfiler, ROCm Systems Profiler,