Research Engineer, Index Intelligence

The role owns the signals and decisions that govern what gets crawled, indexed, refreshed, or dropped across a very large web corpus. A strong candidate brings hands on machine learning work with classifiers, rankers, and calibration, plus solid instincts for messy data at scale. The person must be able to define what a correct answer even means when no ground truth exists, and judge work by whether a decision changes and search improves.How it fits the AI eraThe work sits at the core of how AI systems find and consume information, since models and agents depend on a clean, well chosen index. Much of the judgment is still human: framing what quality and credibility mean, setting up supervision, and connecting a signal to real end to end impact. AI helps build and tune the models, but deciding which pages deserve to exist in the index stays a research and product call.How it builds AI experienceThe role offers direct practice in training and calibrating models for page quality, deduplication, and credibility at web scale, which is applied AI work on real retrieval problems. Building toward it means getting hands on experience with classification and ranking models, evaluation without clean labels, and data pipelines over large corpora. Familiarity with how search and retrieval systems use embeddings and vector indexes would help, given the company builds a search engine and API for AI models and agents.Worth showingClassifier and ranker trainingDefining ground truthEnd to end impact thinkingThis is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.About ExaExa is an applied AI lab that builds a search engine and API for AI models and agents, per the company. #J-18808-Ljbffr