Data/ML/AIDevOps/CloudHigh signalNewAround since 2017
Ray (Distributed Computing)
Also written as Ray Serve, Ray Train, Ray Tune, Ray Data, Anyscale
An open-source framework for spreading Python and AI workloads — data processing, model training, tuning and serving — across many machines. Widely used by companies that train or run their own models at scale. Anyscale is the company behind it.
Think of it like
A foreman who splits a huge job across a whole crew and gathers the results back together.
Junior or senior?
Signals real scale.
Senior sounds like
Has run Ray on a cluster (often on Kubernetes) and can talk about failures, memory problems and cost.
Ask them
“How big was your Ray cluster, what ran on it, and what tended to break?”