Senior Software Engineering Manager, Machine Learning, Maps

Senior Software Engineering Manager, Machine Learning, Maps Share Senior Software Engineering Manager, Machine Learning, Maps _corporate_fare_ Google _place_ Mountain View, CA, USA **Advanced** Experience owning outcomes and decision making, solving ambiguous problems and influencing stakeholders; deep expertise in domain. Share Senior Software Engineering Manager, Machine Learning, Maps _info_outline_ XIn most instances, this position requires in-person interviews as part of the hiring process. **Minimum qualifications:**

• Bachelor’s degree, or equivalent practical experience.
• 8 years of experience programming in C++, Java, Python, Kotlin or Go.
• 5 years of experience in a people management or technical leadership role.
• Experience building and deploying Machine Learning models.
• Experience with Generative AI.

**Preferred qualifications:**

• Master's degree or PhD in Computer Science, or a related technical field.
• 7 years of experience deploying Machine Learning models in production environments.
• Experience with Deep Learning, Computer Vision (e.g., object detection, OCR), and frameworks like TensorFlow or PyTorch.
• Experience with large-scale data processing systems.
• Ability to lead complex technical projects and collaborate with different stakeholders.

**About the job** Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started -- and as a manager, you guide the way. With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally. As an Engineering Manager, you will oversee a team handling complex technical challenges in extracting vital information like speed limits and road signs from massive datasets. Your team leverages Machine Learning (ML) and Computer Vision techniques to directly impact the safety and reliability of mapping and in-car systems used by millions worldwide. This is a unique opportunity to work at the intersection of ML, geospatial data, and the automotive industry, contributing to systems that have real-world impact on how people navigate. 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. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $262000 - $364000 (USD) + 25% bonus target + equity + benefits Learn more aboutbenefits at Google ( . **Responsibilities**

• Lead a team of software engineers designing and deploying machine learning models to extract map features and attributes.
• Set the strategic direction for the group, defining a multi-year technical outlook and aligning stakeholder goals.
• Partner with senior architects to ensure ambiguous systems are driven toward solutions that scale and maintain high reliability.
• Provide technical leadership, mentorship, and performance coaching to technical leads and engineers on the team.
• Review systems designs and product development code to solve complex problems and ensure engineering best practices.

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