Staff Software Engineer, Ads Modeling, Personalization, and Quality
Google · Mountain View, CA
$207,000–$301,000from the description
Jul 10, 2026
Mountain View, CA
Jul 21, 2026
What this job asks for AI summary
A staff-level ML engineering role focused on building and improving deep learning models that predict how users interact with app-based ads across Google's ad delivery channels. Day-to-day work involves designing model architectures, engineering input features from ad creatives and user history, debugging advertiser performance issues, and collaborating with product and partner teams. Suits engineers with substantial ML infrastructure and modeling experience, ideally with a background in advertising or statistical experimentation.
Senior level · 8+ years · San Jose-Sunnyvale-Santa Clara, CA · Full-time
Advertised as Staff, but the requirements read as Senior.
“or” means any one of them counts — you don't need all of them.
Posted 5 times — it's one opening, so apply once.
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Roughly 440 people in the San Jose-Sunnyvale-Santa Clara, CA area plausibly meet what this posting asks for (data scientists). range 330–680
Applicant volume Moderate — A normal amount of company. The rare requirements below are what will separate a shortlisted application from the rest.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $189,150 (middle half $152,859–$224,286). This posting is about at that midpoint.
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.
Why we read it this way (7)
This role sits at the intersection of ML/AI modeling and software engineering. The primary day-to-day work — designing deep learning models, feature engineering, model architecture, and ML infrastructure — maps most closely to Data Scientists (15-2051), though the heavy software engineering framing (8 years SWE experience required, architecture, testing, launching products) makes Software Developers (15-1252) a credible alternative.
The title is 'Staff Software Engineer' but the actual requirements (8 years SWE, 5 years ML) and scope (owning outcomes within a domain, not setting direction across multiple teams) are consistent with a Senior-level role. The 'Staff' designation at Google is a recognized level above Senior, but the JD's scope language ('Advanced Experience owning outcomes') does not clearly demonstrate org-wide cross-team technical authority beyond a single domain.
Compensation is stated as $207,000–$301,000/year plus a 20% bonus target and equity; the bonus and equity are noted separately and not included in the min/max figures.
Degree requirement is marked None because the JD explicitly accepts 'equivalent practical experience' in lieu of a Bachelor's degree.
'Model deployment' and 'model evaluation' are listed as parenthetical examples under the ML infrastructure requirement; they are captured as separate skills given their specificity but derive from the same required bullet.
The preferred qualifications section includes 'data structures and algorithms' with 8 years — this is listed under Preferred, not Required, so it is marked as preferred despite the specific year count.
Ignored 4 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): software development, software design and architecture, data structures and algorithms, technical leadership.
Read the full posting
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