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

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

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.