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Cross-Surface Eval Taxonomy — design the measurement system from scratch on one Product.ai surface, prove substrate-builder phenotype

Pick one Product.ai surface (Alloy, Cortex memory, SimplyCodes code-verification, or Product.ai chat). DESIGN the eval taxonomy from scratch — what to measure, why, how to close the loop from production failure to eval case. Not "ran evals" — designed the taxonomy. Ship the v1 substrate against a paired metric: time-to-runnable-eval AND grader-pass-rate on N=10 unseen variants of a planted failure trace. Document the iteration on metric choice — including the moment the candidate's first metric was wrong and what they replaced it with.

STEP 1 — APPLY

Apply: Cross-Surface Eval Taxonomy — design the measurement system from scratch on one Product.ai surface, prove substrate-builder phenotype

Submit your details below. After this step you'll record a short video questionnaire.

PDF, DOC, or DOCX · max 50MB

A headshot for your candidate card — JPG, PNG, or WEBP · max 8MB. Optional.

A piece of writing or analysis that shows how you think — process doc, system design, deep research. PDF, DOC, or DOCX · max 50MB.

FIT & LOGISTICS

Most of our roles are on-site or hybrid in Santa Monica. We need your own answers here — please don't rely on what's on your LinkedIn.

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Paid trials are contract by default. Pick "Full-time" if you're hoping the trial converts.

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After submitting, you'll be taken to the Hireflix video questionnaire.

If you encounter any issues submitting your application, please reach out to hiring@product.ai.