Berlin · Full-time
Website: https://getclaro.ai/
Companies run on product and supplier data, but that data is usually fragmented across catalogs, PDFs, supplier feeds, PIMs, ERPs and spreadsheets.
Claro turns that mess into reliable product intelligence.
We build systems that identify products across inconsistent sources, extract and validate technical information, resolve duplicates, classify products and create canonical product records with confidence and provenance.
Our customers deal with large, messy, real-world datasets where identifiers are incomplete, descriptions conflict and mistakes have operational consequences.
We are now looking for a Founding Machine Learning Engineer — Model Systems & Evals to help build the intelligence layer behind Claro.
You will own the path from ML experiment to reliable production system.
You will work across retrieval, matching models, embeddings, LLMs, confidence scoring, evaluation, deployment and production feedback.
Your job is not simply to build better models.
It is to build the systems that allow us to answer:
Is this model actually better? Where does it fail? Can we trust it enough to automate this decision? Can we deploy it safely across different customer datasets?
You will work closely with our CTO, data science team and product team, taking ideas from research and customer problems through evaluation and into production.
This is a hands-on role. You will write models, pipelines, APIs, evaluation tooling and production code.
Develop and improve the ML systems behind product identity and entity resolution.
You will work on problems such as: