Software Engineer, Sensing, Perception

Minimum qualifications:

• Bachelor's degree in Computer Science, Electrical Engineering, Mathematics, or Physics, or equivalent practical experience.
• 2 years of experience in software development (e.g., deep learning, perception, or computer vision).
• Experience with Computer Vision (e.g., image classification, image processing, object detection) and Deep Learning either an academic or industry setting.

Preferred qualifications:

• Master's degree or PhD in Computer Science, or in a related technical field.
  
• Experience in Deep learning libraries, e.g., TensorFlow, Pytorch, JAX and working with deep learning models, e.g., ResNet, MobileNet, Transformer architectures.
• Experience in Machine Learning (ML), ideally in the field of perception (object detection, classification, segmentation, etc.).

Experience in developing and deploying production-ready computer vision systems.

Experience working with and deploying models to edge devices or cloud services.

Experience working with resource-constrained environments and edge computing.

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.

In this role, you will work on EdgeSense processes sensor data from Original Equipment Manufacturer (OEM) vehicles to improve coverage of map-related data and improve the user experience.

You will build out an algorithmic foundation to enable a deeper local scene understanding based on available sensors on current vehicle platforms, which also includes Perception. The local scene understanding is leveraged to understand map churn and drive automated map maintenance.

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 $136,000-$200,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. 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

• Support, design and deploy Machine Learning (ML) perception systems for resource-constrained devices.
• Engage with other partner teams on data acquisition and label effortsin a cross-functional setting.
  
• Design systems to measure the real world performanceof Google's models.
  
• Collaborate with teams across Google and external partners.