Staff Software Engineer, Google Ads
Mountain View, CA, USA · Staff+
Sponsorship not specified$207k-$300kDetected 46 min ago
Full-Stack DevelopmentData StructuresNLPUI DesignGoogle AdsLeadership
> stay_score
odds of building a lasting career here
64Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role100
Entry-level history0
PERM / green-card track0
Lottery odds (Level IV)94
Fits your clock70
Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.
Lottery odds assume a STEM candidate.
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About the role
- - Bachelor's degree or equivalent practical experience.
- - 8 years of experience in software development.
Responsibilities
- Manage project priorities, deadlines, and deliverables.
- Design, develop, test, deploy, maintain, and enhance large scale software solutions.
Requirements
- Bachelor's degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience testing, and launching software products.
- 3 years of experience with software design and architecture.
Nice to have
- Master's degree or PhD in Engineering, Computer Science, or a related technical field.
- 8 years of experience with data structures/algorithms.
- 3 years of experience in a technical leadership role leading project teams and setting technical direction.
- 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
- Experience working with advertising platforms.
- Our products need to handle information at massive scale, and extend well beyond web search.
- the list goes on and is growing every day.
- As a software engineer, you will work on a specific project critical to Google's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve.
Compensation
- US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits
Company info
- We also enable Google to engage with customers at scale.
This listing is sourced directly from Google's careers page and normalized into a canonical job model.