Deep Learning Researcher at Ubiquity6

San Francisco, Remote · Full Time

Ubiquity6 is working on some of the most compelling challenges in computer vision and augmented reality. Our mission is to bring people together in physical spaces by building a platform to enable persistent, massively shared augmented reality experiences. Ubiquity6 was founded in 2017 and has raised $37.5M from Benchmark, Index Ventures, First Round Capital, Kleiner Perkins Caufield Byers, and Google’s Gradient Ventures. Ubiquity6 is committed to recruiting, developing and retaining the most talented people from a diverse candidate pool. We have an inclusive workplace that supports the diverse cultures, backgrounds, perspectives, skills, and experiences of every team member.

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Job Description

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.

The Role

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

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What We're Building

We use computer vision to enable massively multiplayer, persistent AR experiences on top of the physical world.

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Ubiquity6 Team

Anjney Midha
CEO @Ubiquity6 • Previously @KPCB @Google • Studied at @Stanford University
Michael Abbott
Apple Former General Partner at KPCB VP Engineering @Twitter SVP Palm (webOS) MS - Azure Founder - Composite Software, Think Passenger
Ankit Kumar
Stanford Mathematics; Machine Learning & Artificial Intelligence; Algorithms
Raven Jiang
Stanford CS, product design, front-end and full stack development, Tech Director of Stanford in Government, Stanford Daily columnist, interned at Dropbox
Ryan Diaz
Software Engineer at Ubiquity6
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Ubiquity6 Investors

Michael Abbott
Apple Former General Partner at KPCB VP Engineering @Twitter SVP Palm (webOS) MS - Azure Founder - Composite Software, Think Passenger
Ray Bradford
Founder & CEO at Spruce. Former Kleiner Perkins Partner, Amazon Web Services product leader. 
Lee Linden
Entrepreneur & Early Stage Investor Founder of @Tapjoy Founder of @Karma Ads/Commerce at @Facebook
Lake Dai
Entrepreneur, Venture Capitalist, Adjunct Professor at Carnegie Mellon University, Advisory Board Member of Women In Technology International (WITI)