InternshipWhat a Inference Engineering intern does
The Inference Engineering role, what you build at each level and what you need before you start.
Make AI models fast and affordable to run: latency and throughput, batching, quantisation, caching, serving frameworks and cost models.
What you build, level by level
- Level 1: Foundations: What inference engineering is, Python and PyTorch setup, Hugging Face pipelines and more.
- Level 2: Building real features: Quantisation, ONNX Runtime, Local LLM serving and more.
- Level 3: Professional work and capstone: vLLM or TGI, Continuous batching, Speculative decoding concept and more.
Where this work is used
Training Trains, W3AppDevelopers and DomainHostly use these skills in real projects: AI / Machine Learning Solutions. Interns who pass the readiness check can take paid-company work from the Company Work board in the portal.
Before you start
Python and basic machine learning. A GPU helps but free cloud notebooks are enough.