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Location
In office (Mountain View)
Seniority
Staff · 8+ years exp
Visa
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Confirmed on the employer's own hiring board on Nov 12, 2026. First seen by Alion on Nov 5, 2026. Google scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Google is an American technology company founded in 1998 by Larry Page and Sergey Brin and now the principal subsidiary of Alphabet, headquartered in Mountain View, California. It operates the world's dominant search engine and the advertising system built around it, along with YouTube, Android, Chrome, Gmail, Maps, Workspace and Google Cloud, reaching billions of users across nearly every internet-connected market. The company designs its own silicon in the Tensor Processing Unit line, develops the Gemini foundation models through Google DeepMind, and derives most of its revenue from advertising while cloud has become its fastest growing segment.

About the job

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.

Search users increasingly expect rich, visual, and personalized content in their AI Mode and AI Overview responses. Our team builds memory and personalization for multimodal queries, including Google Lens traffic and increasingly complex questions that may combine text, images, and other file inputs. Our tech stack combines classic retrieval/ranking of image results with LLM-native visual capabilities.

In Google Search, we're reimagining what it means to search for information - any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally.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.

Responsibilities

  • Set technical strategy and prioritization for the multimodal rich features domain.
  • Solve deep technical issues collaboratively at the intersection of core quality, new features, infrastructural optimizations, and model training.
  • Drive team execution and consistently deliver on top-line metrics.
  • Spot opportunities proactively to connect the dots across multiple workstreams.
  • Accelerate team members' career growth by establishing next-level scope and providing regular coaching.

Qualifications

Minimum qualifications:

  • Bachelor’s degree or equivalent practical experience.
  • 8 years of experience in software development.
  • 5 years of experience in a technical leadership role, and 5 years managing people.
  • 5 years of experience leading design for machine learning products and optimizing systems that incorporate machine learning.
  • Experience integrating generative AI tools or large language model (LLM) interfaces into workflows.

Preferred qualifications:

  • Experience supporting and developing the careers of engineering team members.
  • Experience working on user-facing machine learning products.
  • Experience setting technical direction and scaling technical impact on software engineering teams.
  • Experience in data analysis with a metrics-first perspective and quality evaluation.
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