Senior Staff Software Engineer, Full Stack
- Location
- Zürich, Switzerland; New York, NY, USA
- Work model
- On-Site
- Level
- Staff
- Salary
- $262k – $364k/yr
- H-1B history
- 2,460 approvals (FY2023)
- Posted
- 11h ago
Skills
About this role
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; 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. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward. With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions. As we enter the age of AI transformation on search, we have a need to improve the user understanding, advertiser intent and LTV value definition to power automated value delivery for retailers. Google Ads is helping power the open internet with the best technology that connects and creates value for people, publishers, advertisers, and Google. We’re made up of multiple teams, building Google’s Advertising products including search, display, shopping, travel and video advertising, as well as analytics. Our teams create trusted experiences between people and businesses with useful ads. We help grow businesses of all sizes from small businesses, to large brands, to YouTube creators, with effective advertiser tools that deliver measurable results. We also enable Google to engage with customers at scale. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $262000 - $364000 (USD) + 25% bonus target + equity + benefits Learn more about benefits at Google .
Own the technical and strategic roadmap for retail signals, goals and optimization. Improve the user understanding, advertiser intent and LTV value definition to power automated value delivery for retailers. Work with PMs and executives, identify the right areas of improvements, making sure all the areas come together. For example, how we consolidate different tools for value adjustments and use consistently across predictions and optimization. Work with senior cross-product area partners to leverage their expertise and infrastructure.
Minimum qualifications: Bachelor's degree or equivalent practical experience.
8 years of experience in software development. 7 years of experience with full stack development, across back-end such as Java, Python, GO, or C++ codebases, and front-end experience including JavaScript or TypeScript, HTML, CSS or equivalent. 5 years of experience with design and architecture; and testing/launching software products. 3 years of experience in performance analysis including large-scale distributed systems, machine learning optimization and performance optimization. Experience in machine learning and performance optimization. Preferred qualifications: Deep understanding of performance optimization within a constrained environment. Familiarity with how AI-driven signals and ML models translate into retail-specific business value and user-facing improvements. Ability to synthesize complex datasets and various performance metrics into actionable strategic insights and clear technical roadmaps. Ability to navigate ambiguity and "connect the dots" across various product areas to build a cohesive, long-term vision for retail advertising. Ability to balance trade-offs between automated value delivery and system limitations. Proven track record of leading complex,