Charles Frye
VERIFIED TECHNICAL DOSSIERSources checked

Charles Frye

AI Infrastructure Engineer

2 Verified ArtifactsSource Checked & Attributed

Verified Proof of Work Artifacts

2 items cataloged

Each artifact below represents an authenticated research publication, production code repository, or technical architectural framework directly authored or co-created by Charles Frye. Every entry undergoes editorial source verification.

#1
EXPLANATION Checked Sep 20, 2026

The Full Stack LLM Bootcamp: End-to-End Enterprise LLM Production Engineering

Designed and delivered the comprehensive Full Stack LLM Bootcamp, educating tens of thousands of software engineers on prompt design, fine-tuning with LoRA/QLoRA, vector retrieval, evaluation metrics, and cost-efficient deployment.

Model & Execution Context:PyTorch, Hugging Face, vLLM, LangChain, Modal serverless GPU runtimes.
Scope & Limitations

Rapid evolution in model capabilities requires constant curriculum revisions to address frontier tool-calling interfaces.

#2
IMPLEMENTATION Checked Sep 20, 2026

Serverless High-Throughput vLLM Inference Container Orchestration on Modal

Engineered containerized serverless LLM deployment architectures on Modal, orchestrating multi-GPU vLLM inference with cold-start mitigation, dynamic batching, and automated autoscaling from 0 to 100 NVIDIA A100/H100 instances.

Model & Execution Context:Modal Python SDK, CUDA 12, PagedAttention, Tensor Parallelism across NVLink clusters.
Scope & Limitations

Cold-start container image pulling and model weight downloading require warm snapshot caching techniques to maintain sub-second response readiness.