Inference engineering is the discipline of optimizing how AI models serve predictions in production, covering the full stack from CUDA kernels to multi-cloud infrastructure. As open models like DeepSeek and Llama reach parity with closed models, more engineering teams can now apply inference engineering to reduce latency, cost,
Table of contents
1. Setting the stage: why is inference so important?2. What is inference?3. When is inference engineering needed?4. What hardware does inference use?5. What software does inference use?6. What infrastructure does inference need?7. Five approaches to make inference fasterTakeawaysSort: