Description

Minimum qualifications:

• Bachelor's degree in Computer Science or related technical field, or equivalent practical experience.
• 8 years of experience in software development.
  
• 7 years of experience leading technical project strategy, ML design, and working with industry-scale ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
• 5 years of experience with design and architecture; and testing/launching software products.
  
• Experience with Generative AI technologies (e.g., LLM capabilities and applications).
• Experience working on search quality.

Preferred qualifications:

• 8 years of experience with data structures/algorithms.
• 5 years of experience in a technical leadership role leading project teams and setting technical direction.
  
• 5 years of experience in Machine Learning, LLM and GenAI.
• 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
• Experience with data analysis, quality, and experimentation.

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.

As a senior software engineer, you will drive the end-to-end quality of Generative AI features and products in Search (e.g. AI Overview, AI Mode, etc.). You will focus on understanding and improving measurement and full stack integrations to improve factuality, grounding, helpfulness, and trust in Search.

You will have the opportunity to directly impact answer quality, to the benefit of billions of users. You will be balancing user-facing quality, metrics, and infrastructure work, and is comfortable with both the technical implementation and the quality and analysis components of the role.

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.

The US base salary range for this full-time position is $248,000-$349,000 bonus equity benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

• Design, develop, test, deploy, maintain, and enhance large scale software solutions.
  
• Provide technical leadership on high-impact projects. Manage project priorities, deadlines, and deliverables.
  
• Facilitate alignment and clarity across teams on goals, outcomes, and timelines. Influence and coach a distributed team of engineers.
  
• Improve measurement, running experiments, ensuring launches continue to remain effective and protecting against regressions.
• Make strategic decisions on when to leverage Large Language Model (LLM) technology compared to existing processes.

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Requisition #: 97293470518911686

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