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 be part of the XR Semantic Perception team, which develops novel core technology around computer vision and ML, with a particular focus on scene and object understanding and 3D computer vision. You will work across the full range from research to product, as part of a team composed of Research Scientists and Software Engineers, serving multiple perception-related products at Google, with a particular focus on XR products and applications.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 5 years of experience with software development in one or more programming languages.
- 3 years of experience with Computer Vision (image classification and processing, object detection, visual search), video generation, or signal processing; and experience designing Computer Vision systems.
- 3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging).
- Publication record in AI conferences (e.g., NeurIPS, CVPR, ICCV, ICLR).
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical field.
- Experience working in an industry or academic research lab, focusing on multiple aspects of the "research to product" pipeline, particularly model optimization and efficiency improvements.
- Familiarity with generative AI techniques, such as image diffusion models, and their application to visual enhancement.
- Strong background in 3D computer vision and deep learning, with specific, proven expertise in Gaussian Splatting (3DGS), Neural Radiance Fields (NeRF), and 3D scene reconstruction.