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Confirmed on the employer's own hiring board on Nov 10, 2026. First seen by Alion on Nov 10, 2026. Google scores B on the Alion truth index.

Overview
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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.

The Search Intelligence Trust team ensures the integrity of Google's advanced Search features, including AI Overviews and classic ranking. We maintain Google's high bar for accuracy and safety as Generative AI scales, bridging foundation models with rigorous quality standards. We develop robust algorithmic safeguards to protect users against misleading narratives, low-quality content, and synthetic hallucinations.

As a Software Engineer, you will scale our multimodal safety stack by combining large-scale backend engineering with applied AI. You will build classifiers and protection systems safeguarding billions of users. This role requires strong engineering fundamentals, investigative judgment for complex quality trade-offs, and the ability to iterate rapidly.

Join Google Search AI and work at the intersection of industry leading

global scale. We apply breakthrough research, leveraging models like Gemini, to launch high-impact products that help billions ask any question and get things done. If you want to drive the future of AI in Search and work with world-class experts to deliver tangible, global impact and continuous innovation, this is the place.

Responsibilities

  • Implement GenAI solutions, utilize ML infrastructure, and contribute to data preparation, optimization, and performance enhancements.
  • Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
  • Analyze large-scale experimental results, develop evaluation frameworks balancing helpfulness and safety, and drive launches from conception to production.

Qualifications

Minimum qualifications:

  • Bachelor’s degree or equivalent practical experience.
  • 2 years of experience with software development in one or more programming languages (C++, Python, Kotlin).
  • 1 year of experience with end-to-end Machine Learning (e.g., model deployment, model evaluation, data processing, debugging).
  • Experience in launching Machine Learning or AI products from research to production.
  • Experience designing, building, and operating large-scale distributed systems, with a focus on scalability, fault tolerance, and reliability.

Preferred qualifications:

  • Master's degree or PhD in Computer Science or related technical fields.
  • 2 years of experience with data structures and algorithms.
  • Experience in building and architecting ML systems and infrastructure (e.g., for model training, evaluation, deployment, serving).
  • Experience with core GenAI concepts (LLM, Multi-Modal, Large Vision Models).
  • Experience with large-scale A/B experiments.
  • Experience designing, building, and debugging high-throughput backend systems, particularly involving AI model deployment.
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