Machine Learning Engineer; Intern

Most of the machine learning work that reaches production is not modelling. It is knowing which failures matter, building the evidence that shows whether they still happen, and being able to defend that evidence to someone whose job is to find the hole in it.

You will own model development and evaluation on client engagements, largely in regulated settings: federal health, prime contractors, enterprises with data that cannot leave their boundary. That means working against real constraints on residency and access rather than a clean benchmark, and writing up what you found in a form a review board can read.

This role suits someone who has shipped a model that other people depended on, and who has opinions about why aggregate accuracy is a poor summary of anything.

This opportunity is for the Machine Learning Engineer (Intern) role at Theory AI.