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

AMD is a technology company advancing processors, AI, and related computing technologies. The company is seeking PhD AI Model Optimization & Software Engineer Interns/Co-ops to develop, benchmark, optimize, and evaluate AI software across CPUs, GPUs, and accelerators, while contributing to frameworks, runtimes, distributed systems, compiler technologies, and AI infrastructure.

What you'll do:

• 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 technologies such as 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 the 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

What they're looking for:

• 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 one or more of the following areas:
• 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

Benefits:

• Hybrid or onsite work structure