2027 PhD AI Systems & GPU Performance Engineering Intern

AMD
San Jose, Santa Clara
Workplace: HybridInternshipFunction: Research & Scientific (R&D)Education: phdSkills: ["Profiling analysis","Performance analysis","Data-driven recommendations","Benchmarking"]

Help optimize AI training workflows and inference applications on AMD Instinct GPUs by profiling and benchmarking compute, memory bandwidth, communication, and kernel execution. Develop reproducible benchmarking frameworks and automation scripts across AI models and software stacks. Analyze end-to-end LLM and generative AI performance, applying techniques like operator fusion, scheduling, mixed precision, and quantization while partnering with engineers and researchers to improve efficiency and scalability.

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FursaFursa
AMD
AMD
14 hours ago

2027 PhD AI Systems & GPU Performance Engineering Intern

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Source: Company careers pageValidated by: Fursa AI
Last checked: 2 hours agoStatus: Live

Job Summary

Help optimize AI training workflows and inference applications on AMD Instinct GPUs by profiling and benchmarking compute, memory bandwidth, communication, and kernel execution. Develop reproducible benchmarking frameworks and automation scripts across AI models and software stacks. Analyze end-to-end LLM and generative AI performance, applying techniques like operator fusion, scheduling, mixed precision, and quantization while partnering with engineers and researchers to improve efficiency and scalability.
Location: San Jose, Santa Clara
Workplace: Hybrid
Employment Type: Internship
Job Function: Research & Scientific (R&D)
Seniority: Intern level

Key Responsibilities

  • •Optimize AI training and inference workloads on AMD Instinct GPUs by profiling, benchmarking, and identifying bottlenecks across compute, memory bandwidth, communication, and kernel execution.
  • •Develop reproducible benchmarking frameworks and automation scripts for performance validation across AI models, software stacks, runtimes, drivers, and accelerator platforms.
  • •Analyze and optimize end-to-end AI workflows for LLMs and generative AI applications, exploring model optimization techniques such as operator fusion, scheduling strategies, mixed precision, and quantization.
  • •Evaluate GPU performance with engineers and researchers, comparing workload characteristics across hardware and software environments.
  • •Contribute data-driven recommendations to improve efficiency, scalability, throughput, latency, and overall system utilization.

Key Requirements

  • •Currently pursuing a PhD in Computer Science, Computer Engineering, Electrical Engineering, Applied Mathematics, or a related field, with graduation after the internship ends.
  • •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 training and inference concepts.
  • •Experience working in Linux, including scripting, debugging, profiling, and performance analysis.
  • •Familiarity with profiling and benchmarking methodologies and tools such as ROCm Systems Profiler, rocProfiler, Omniperf, or Nsight, plus interest in AI model optimization (e.g., quantization, mixed precision, distributed training).
Experience:AI
Education:PhD / Doctorate
Skills:Profiling analysisPerformance analysisData-driven recommendationsBenchmarking
Languages:English
Tech Stack:PythonC/C++CUDAHIPTritonROCmROCm Systems ProfilerRocProfilerPyTorchJAXTensorFlowVLLMLinuxOmniperfNsight

Eligibility

Work Authorization:Authorization required. Sponsorship not provided.

Company Brief

AMD
Designs and produces semiconductor products including CPUs, GPUs, and adaptive SoCs for consumer, enterprise, and embedded markets, competing across PCs, data centers, and gaming industries.
Industry: Electronics Manufacturing
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Santa Clara, United States
Founded: 1969
Glassdoor
Glassdoor: 3.9
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