2027 PhD AI Model Optimization & Software Engineer Intern/Co-op

AMD
Austin
Workplace: HybridInternshipFunction: Software EngineeringEducation: phdSkills: []

Work on AI model optimization and software engineering projects at the heart of AMD’s AI ecosystem. You’ll develop, benchmark, and optimize training, fine-tuning, and inference across CPU/GPU/accelerator platforms, profile and remove bottlenecks, and prototype optimized kernels using HIP, CUDA, OpenCL, or Triton. You’ll also contribute to AI frameworks and runtimes (e.g., PyTorch, TensorFlow, JAX, ONNX Runtime, vLLM, SGLang), plus parallel/distributed and MLOps-style tooling.

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FursaFursa
AMD
AMD
2 days ago

2027 PhD AI Model Optimization & Software Engineer Intern/Co-op

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Source: Company careers pageValidated by: Fursa AI
Last checked: 3 hours agoStatus: Live

Job Summary

Work on AI model optimization and software engineering projects at the heart of AMD’s AI ecosystem. You’ll develop, benchmark, and optimize training, fine-tuning, and inference across CPU/GPU/accelerator platforms, profile and remove bottlenecks, and prototype optimized kernels using HIP, CUDA, OpenCL, or Triton. You’ll also contribute to AI frameworks and runtimes (e.g., PyTorch, TensorFlow, JAX, ONNX Runtime, vLLM, SGLang), plus parallel/distributed and MLOps-style tooling.
Location: Austin
Workplace: Hybrid
Employment Type: Internship
Job Function: Software Engineering
Seniority: Intern level

Key Responsibilities

  • •Develop, benchmark, and optimize AI software for training, fine-tuning, and inference across CPU, GPU, and accelerator platforms.
  • •Profile AI workloads to identify hardware and software bottlenecks and implement performance improvements across compute, memory, communication, framework, and runtime layers.
  • •Design, prototype, and optimize GPU or CPU kernels using technologies such as HIP, CUDA, OpenCL, Triton, or related accelerator programming models.
  • •Research and implement AI model optimization methods including quantization, low-precision inference, sparsity, pruning, distillation, and parameter-efficient fine-tuning.
  • •Contribute to AI frameworks, libraries, execution runtimes, and deployment technologies such as PyTorch, TensorFlow, JAX, ONNX Runtime, vLLM, or SGLang.

Key Requirements

  • •Currently enrolled in a U.S.-based PhD program in Computer Science, Computer Engineering, Artificial Intelligence, Machine Learning, Electrical Engineering, or a related technical field.
  • •Programming experience in Python and/or C/C++.
  • •Experience with one or more AI frameworks or runtimes such as PyTorch, TensorFlow, JAX, ONNX Runtime, vLLM, or SGLang.
  • •Experience in AI model inference, training, fine-tuning, or performance optimization (via experience, coursework, research, or projects).
  • •Familiarity with software development tools such as Git, CMake, Make, Conda, Docker, or related build technologies.
Experience:PhDAIMachine learning
Education:PhD / Doctorate in Computer Science, Computer Engineering, Artificial Intelligence, Machine Learning, Electrical Engineering (or related technical field)
Languages:En-us
Tech Stack:PythonC/C++PyTorchTensorFlowJAXONNX RuntimeVLLMSGLangHIPCUDAOpenCLTritonGitCMakeMakeCondaDockerCI/CD

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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