Rhys Williams
Lead AI Engineer at WeCloudData
Old Toronto, Ontario, Canada
Summary
👤
Senior🎓
Top SchoolRhys Williams is a Lead AI Engineer with nine years of cross-disciplinary experience specialising in large-scale computation, model quantization, and edge deployment. He has led production-grade RAG systems, multi-agent toolsets and distributed training pipelines using DDP, ZeRO, Ray/Kuberay and Triton optimisations. His background spans embedded NVIDIA Jetson/Orin work, microcontroller-driven creative tech for live events, and practical model compression for CPU and edge-first products. Rhys combines hands-on kernel and inference tuning (flash/sparse attention, fused softmax, Triton kernels) with team leadership, curriculum development and advisory roles. Based in Old Toronto, he’s equally at home reconstructing foundation model architectures as he is orchestrating hyperparameter and reinforcement learning at scale, often bridging research ideas into deployable, resource-efficient systems.
9 years of coding experience
9 years of employment as a software developer
Ba (Hons) Political Sociology, Political Science and Government, 2:1, Ba (Hons) Political Sociology, Political Science and Government, 2:1 at Lancaster University
Github Skills (82)
voice-commands10
tflite10
yolov510
onnx10
object-detection10
line-segment10
detector10
ultralytics10
pytorch10
voice-control10
machine-learning10
coreml10
yolov410
yolov89
classifier9
Programming languages (5)
Github contributions (5)
rhysdg/vision-at-a-clip
Jun 2024 - Sep 2024
Low-latency ONNX and TensorRT based zero-shot classification and detection with contrastive language-image pre-training based prompts
Contributions:20 PRs, 123 pushes, 12 branches in 3 months
clipfoundation-modelsgrounding-dinomachine-learningonnx
rhysdg/haystack-experimental
Nov 2024 - Feb 2025
🧪 Experimental features for Haystack
Contributions:4 PRs, 31 pushes, 3 branches in 2 months
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