Computer Vision / Machine Learning Engineer at 8th Wall
Palo Alto, CA, US


Interested in Augmented Reality? Do you want to be part of a team that is changing the way the world interacts with mobile devices?  We are an all-star team working to pioneer the next wave of technology - reimagining the way the world interacts with technology today. 8th Wall’s mission is to break the wall between the digital and physical worlds, and we’re hard at work to bring augmented reality technology into the hands of developers worldwide.


As a Computer Vision / Machine Learning Engineer you’ll work closely with other engineers on our team to bring industry leading algorithms to a potential market of billions of smartphone users. We are looking for experienced, production-focused engineers who want to develop highly reliable products in a collaborative fast-paced environment.




  • Design, train, test, deploy, maintain and optimize ML-based computer vision solutions.
  • Manage individual projects, systems and deliverables.


Minimum qualifications


  • MS or Ph.D. with a focus on computer vision or machine learning, or equivalent work experience.
  • 2+ years of experience with computer vision or machine learning frameworks and libraries.
  • 2+ years of relevant research or professional experience in software development.
  • Research or professional coding experience in C/C++.


Preferred qualifications


  • Hands on experience with deep learning engines, e.g. TensorFlow, Caffe, Torch, Theano or similar.
  • Extensive experience with data visualization e.g. in Python, Matlab, or highgui/viz.
  • 1+ year of experience with modern CNN/RNN construction (ResNet, Inception, LSTM, etc.).
  • Demonstrated examples of end to end projects for real world, real time applications.
  • Projects in computational geometry, linear algebra, convex optimization, HMM/POMDP, etc.
  • Experience that combines both machine learning and computer vision.


Bonus points


  • Extensive experience with computer vision libraries like OpenCV.
  • Experience with sensor fusion (IMU+vision) for tracking and mapping applications.
  • Experience porting ML or computer vision runtimes to GPU architectures.