Ubiquity6 is working on some of the hardest challenges in computer vision and augmented reality to bring the Internet into the physical world. Ubiquity6 was founded in 2017 by alums of Stanford, Metamind, Facebook, Tesla and Twitter, and is backed by First Round Capital, Gradient Ventures (Google), A&E Networks and Kleiner Perkins.
Ubiquity6 is building infrastructure for shared, ubiquitous AR using computer vision. We believe that giving everyday smartphones the ability to semantically understand depth, geometry and scenes can unlock valuable new ways for humans to interact with each other and the physical world around us.
We are a team of engineers and designers from Metamind, Facebook, Tesla, Twitter and Stanford, and are backed by Google, Kleiner Perkins and First Round Capital, as well as a group of industry leaders including Richard Socher, Bing Gordon and John Doerr.
We are looking for a talented deep learning engineer with computer vision experience to join our small but fast growing team. Ubiquity6 is assembling one of the world’s largest datasets of 3D mapping data, and want you to help us learn from it. You will have ownership of a broad mandate of novel 3D deep learning techniques, with applications in semantic segmentation, 3D object classification, pose estimation, geometry prediction, and more.
- Implementing novel algorithms in standard research-oriented frameworks of your choosing (PyTorch, MXNet, etc)
- Developing new approaches to solve the problem of deep learning on fundamentally 3-dimensional inputs
- 1-2 years of experience in deep learning, 5+ computer science development work overall
- Experience applying deep learning to computer vision problems
- Familiarity with common deep neural net architectures relevant to understanding and synthesizing images
- Ability to work independently and write clean, stable code
- BS, MS, or PhD in Computer Science or a similar field
We use computer vision to enable massively multiplayer, persistent AR experiences on top of the physical world.