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Open nowFirst seen 3 hours ago

Senior Software Engineer, Multimodal Search Quality

Google3,280 open roles

Where
Mountain View, CA, USA
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Your applicationOpen nowSenior Software Engineer, Multimodal Search QualityGoogle · Mountain View, CA, USA

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on Google's own form.

The reply lands in your private mailbox

3×more interviews than doing it yourself with ChatGPT.

The clock on this job

Early applications get read.

8.2% of postings close within 7 days. Measured by our own scanner across the market. Google postings stay open a median of 27 days.

Share of postings closed within
  1. 1.9%1 day
  2. 3.8%3 days
  3. 8.2%7 days
  4. 15.2%14 days
  5. 34.1%30 days
This job: first seen 3 hours ago

Google median: 27 days open

The posting

In most instances, this position requires in-person interviews as part of the hiring process.

Minimum qualifications:

  • Bachelor’s degree or equivalent practical experience.
  • 5 years of experience programming in Python or C++.
  • 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
  • 3 years of experience with techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).
  • Experience integrating generative AI tools or LLM interfaces into workflows.

Preferred qualifications:

  • Master's degree or PhD in Computer Science, or related technical field.
  • 5 years of experience with data structures and algorithms.
  • 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
  • 1 year of experience in a technical leadership role.
  • Experience developing and maintaining automated LLM evaluation pipelines (e.g., autoraters, LLM-as-a-judge, benchmark test harnesses, synthetic data generation).

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.

We are leveraging the foundational capabilities of Large Language Model (LLMs) to revolutionize Search—enabling users to easily ask contextual questions and provide high-quality AI answers. As part of the team, our mission is to make Google Search more helpful by seamlessly answering questions based on users' context. By providing new ways to ask questions, we create new moments to search.

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: $174000 - $252000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

  • Write and test product or system development code.
  • Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.
  • Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
  • Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
  • Drive modeling work to bring LLM to Search, developing evaluation pipelines, core infrastructure/system architecture.
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