Roblox Guest Blog: Fast and Efficient Online Model Serving

Younes Abouelnagah, a Principal ML Engineer at Roblox, shares how his team scaled their online NLP ML model inference on CPU machines and reduced latency using Ray, a distributed computing framework for Python. The blog post details the process of scaling up and out, reducing latency and CPU usage while maintaining civility on the platform by running user-generated content through multiple models. It highlights key learnings in using Ray Core to scale the serving of ML models with very low latency requirements, including setting up a dedicated Ray cluster for improved performance and efficiency.

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