Build the infrastructure of the AI-powered future. The AI Engineering Department trains students to design, deploy, and scale intelligent systems — from model training pipelines to real-time production inference.
4-year program covering software engineering, AI systems design, and production deployment at scale.
2-year graduate program for engineers seeking to lead AI infrastructure and research at scale.
The AI engineering landscape, tools, and the end-to-end model lifecycle.
CI/CD for ML, model versioning, A/B testing, and production monitoring.
Distributed training, parameter servers, data parallelism, and fault tolerance.
Low-latency serving, streaming inference, batching strategies, and SLA management.
Fine-tuning, RLHF, RAG architectures, and serving large language models at scale.
CUDA programming, kernel optimization, memory hierarchies, and mixed-precision training.