Software Engineer III, Computer Vision, Map Geometry

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 ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
  
• 1 year of experience with Computer Vision (e.g., image classification and processing, object detection, visual search), video generation, or signal processing.

Preferred qualifications:

• Master's degree or PhD in Computer Science or a related technical field.
• 2 years of experience with data structures and algorithms.
• Experience developing accessible technologies.
• Experience developing multimodal machine learning systems and optimizing performance using C++ and LLVM, with proficiency in JAX-RS for service-level integration.
• Proficiency in code and system health, diagnosis and resolution, and software test engineering.

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 Map Geometry team is at the forefront of Artificial Intelligence automation for the creation and maintenance of the world's map geometry. In this role, you will leverage Generative Artificial Intelligence techniques to automate the extraction and refinement of map features from data sources like aerial and satellite imagery. This work directly impacts core Google products such as Navigation and Auto alongside a growing number of internal generative AI initiatives.

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

• Design, develop, train, evaluate, and deploy machine learning models for geospatial feature extraction and analysis.
  
• Analyze and experiment with different ML techniques and architectures to improve model performance, robustness, and efficiency.
• Collaborate with client engineers, researchers (e.g., GDM, Google Research), and product managers to define requirements, develop solutions, and land models and automated map edits into production systems.
• Contribute to the full model development lifecycle, including data preparation, training, validation, deployment, and monitoring.
• Stay up-to-date with the latest advancements in machine learning and computer vision.