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Research Software Engineer, Computer Vision

Google
1 day ago
Full-time
On-site
Zürich, ZH

JobsCloseBy Editorial Insights

Google is hiring a Research Software Engineer in Computer Vision for onsite Zurich to join the XR Semantic Perception team, focused on 3D scene understanding and reconstruction for XR products. The role spans research to product, covering Gaussian Splatting, Neural Radiance Fields, pose estimation, and novel view synthesis, with emphasis on model efficiency, training stability, and scalable pipelines, plus ML infrastructure from deployment to evaluation. Requirements include a degree with five years of software development, three years in CV or related signal processing, three years in ML infra, and a publication record. Preferred qualifications include an advanced degree, experience in research labs, and expertise in diffusion models and 3D vision. To apply, tailor your CV to show end-to-end impact, quantify results, cite publications, and show stakeholder collaboration and willingness to relocate to Zurich.

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.

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 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.

Responsibilities

  • Develop innovative computer vision and machine learning technology focused on 3D reconstruction, pose estimation, and novel view synthesis for XR applications.
  • Drive the research, development, and optimization of 3D scene representation pipelines (such as Gaussian Splatting and Neural Representations), including improving model efficiency, training stability, and visual fidelity for large-scale scenes.
  • Establish and maintain relationships with main stakeholders and keep recurring updates on the advancements of the project, making sure that their expectations are aligned to the research and engineering work.