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August 5, 2025

Technical Lead Software Engineer, LearnX Search, AI Overviews

Senior • On-site

$197,000 - $291,000/yr

New York, NY

Minimum qualifications:

  • Bachelor’s degree or equivalent practical experience.
  • 8 years of experience in software development.
  • 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
  • 5 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
  • 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).

Preferred qualifications:

  • Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
  • 8 years of experience with data structures/algorithms.
  • 3 years of experience in a technical leadership role leading project teams and setting technical direction.
  • 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.

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.

Over the last two years, there's been an incredible amount of innovation in the Education x AI space. Inspired by the new frontiers, our LearnX team has been rethinking how people can learn with AI. Joining this team provides an opportunity to build transformative products which will change how billions of users learn globally. We are looking for an applied AI/ML and quality lead to join this exciting, fast evolving space, to help our team rapidly design, prototype, experiment and launch new products. This role provides the unique opportunity to use AI to both improve Search, and bring uniquely valuable educational experiences to Search's users.

The US base salary range for this full-time position is $197,000-$291,000 + 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

  • Lead a team of engineers to define and execute EDU AI Overview products in Search.
  • Collaborate with Product Managers, Engineering Managers, and other leads to define and iterate on projects in a product and technical landscape.
  • Contribute to and make individual contributions to Search's full-stack technical designs, with a particular focus on quality and machine learning.
  • Delegate tasks, set direction, and unblock junior Software Engineers with the help of managers.
  • Collaborate effectively with engineering leaders across Search, Lens, LearnX, GDM, and other teams, while also demonstrating a passion for self-learning and sharing knowledge about Large Language Models (LLMs) as they apply to Search products.