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September 18, 2025

Software Engineer III, AI/ML, Visual Lanes

Mid • On-site

$141,000 - $202,000/yr

Mountain View, CA

Minimum qualifications:

  • Bachelor’s degree or equivalent practical experience.
  • 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
  • 1 year of experience with one of the following AI/ML techniques: Generative AI, Computer Vision, Natural Language Processing (NLP), information retrieval, or specialization in another ML field.
  • 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
  • Experience in data analysis.

Preferred qualifications:

  • Master's degree or PhD in Computer Science or related technical fields.
  • Experience in computational geometry.
  • 2 years of experience with data structures or algorithms.
  • Experience developing accessible technologies.

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 Geo org works to build a beautiful navigation map stitching together multiple data types: advanced road geometry, lane geometry, lane and road markings, intersections, lane restrictions, medians, buildings, etc. Our team is responsible for the data quality of road and lane data attributes and the construction of geometries used to render roads with richer lane details.

We're looking for an engineer with full stack expertise to advance the state of the art in mapmaking in Geo. This role requires the application of cutting-edge GenAI and ML solutions in combination with classical geometric algorithms to power Geo’s next-generation navigation experiences. You'll use your technical expertise in the applied ML and computational geometry domain to not only develop models but also apply them to build practical, scalable solutions worldwide.

The Geo team is focused on building the most accurate, comprehensive, and useful maps for our users, through products like Maps, Earth, Street View, Google Maps Platform, and more. Every month, more than a billion people rely on Maps services to explore the world and navigate their daily lives.

The Geo team also enables developers to use the power of Google Maps platforms to enhance their apps and websites. As they plot a course for the future of mapping, they are solving complex computer science problems, designing beautiful and intuitive product experiences, and improving our understanding of the real world.

The US base salary range for this full-time position is $141,000-$202,000 + 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

  • Write product or system development code. 
  • 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,)
  • Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
  • Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
  • Implement solutions in one or more specialized ML areas, utilize ML infrastructure, and contribute to model optimization and data processing.