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

AMD· AI/Software Engineering
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Austin, TX$91.5kUNAVAILABLEPosted 4w ago

About the role

Intern/Co-op position at AMD in Austin, TX focusing on AI model optimization and software engineering across AI frameworks, runtimes, and accelerator platforms. Full-time onsite internship/co-op with multiple term lengths including Spring/Summer and Summer/Fall options for PhD students or advanced-level candidates.

Responsibilities

  • Develop, benchmark, and optimize AI software for training, fine-tuning, and inference across CPU, GPU, and accelerator platforms.
  • Profile AI workloads, 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 HIP, CUDA, OpenCL, Triton, or related accelerator programming models.
  • Research and implement AI model optimization methods such as 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.
  • Develop or evaluate parallel and distributed computing methods, including collective communication operations and scalable training or inference techniques.
  • Explore compiler, graph optimization, kernel-generation, and runtime technologies that improve efficiency and portability of AI workloads.
  • Build automated evaluation systems, containerized development environments, CI/CD pipelines, internal tools, and developer productivity solutions for AI workflows.
  • Use AI-assisted development tools and coding agents to support software development, testing, debugging, and optimization.
  • Collaborate with software engineers, researchers, architects, platform teams, and project stakeholders to advance next-generation AI software capabilities.

Qualifications

  • 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, coursework, research, or project work in AI model inference, training, fine-tuning, or performance optimization; quantization, low-precision computing, sparsity, pruning, or distillation; GPU or accelerator kernel development; AI frameworks, libraries, compilers, graph optimization, or execution runtimes; performance profiling, benchmarking, debugging, or workload analysis; parallel computing, distributed systems, or collective communications; MLOps, DevOps, automated evaluation, CI/CD, or containerized environments; AI-assisted coding, coding agents, or agentic development workflows.
  • Familiarity with software development tools such as Git, CMake, Make, Conda, Docker, or related development and build technologies.
  • Research publications, preprints, open-source contributions, or participation in the AI and machine learning developer community are preferred but not required.

Skills

Required:PythonC/C++AI frameworks/runtimes
Nice to have:GPU/Accelerator kernel developmentPerformance profiling & optimizationMLOps/CI/CD/containerized envs

Benefits

  • AMD benefits at a glance
Last updated Oct 15, 2026. Interested? Apply on the company site.
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