Senior Machine Learning Engineer, Growth

Waymo, San Francisco, CA +3

What you will do

Own the feature layer between the Growth DB and the models. Work with data engineering on schema design for ML features, and with data science to turn their feature lists into versioned feature definitions that training and scoring both read from.
Build point-in-time correct training data, so a retrain sees each day as it was and does not leak future data. Data science has already named this as a gap in today's pipelines.
Take models data science has trained and put them into production: validate against the offline results, wire them into batch scoring, and add input and output checks that stop a bad run before promos go out.
Lead training automation:

Waymo, San Francisco, CA +3

$175K–$215K

a year

This base pay is below the median for senior ML and AI engineering jobs in the Bay Area.

We compare the middle of each posted range. This is base pay as posted. The group does not include this job.

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Own the feature layer between the Growth DB and the models. Work with data engineering on schema design for ML features, and with data science to turn their feature lists into versioned feature definitions that training and scoring both read from.
Build point-in-time correct training data, so a retrain sees each day as it was and does not leak future data. Data science has already named this as a gap in today's pipelines.
Take models data science has trained and put them into production: validate against the offline results, wire them into batch scoring, and add input and output checks that stop a bad run before promos go out.
Lead training automation: