The job entails developing and implementing various deep learning algorithms for object detection and robust reactive robot control systems. Strong understanding of fundamentals in machine learning especially deep learning is necessary. Along with developing algorithms you will work with the team to maintain a data acquisition system that will be used to train and test algorithms used. The individual will work in a fast paced, dynamic environment with a team of creative, high-performance engineers. Company will sponsor H1B and Green Cards.
• Minimum 2 years relevant algorithm implementation experience.
• Good grasp of Python and C++.
• C# and .NET and some knowledge of CUDA would also be nice to have.
• Ph.D. in Computer Science, Electrical Engineering, or Applied Mathematics.
• Thorough knowledge of Neural Networks particularly, Convolutional Neural Networks (CNN's), Recurrent Neural Networks(RNN) for Object Detection and other general Computer Vision applications.
• Thorough knowledge of Probability and Statistics, Linear Algebra and Computer Science fundamentals.
• Familiarity with Clustering Techniques and wider Machine Learning techniques both supervised and unsupervised.
• Experience in Machine Learning libraries such as Tensorflow, Torch or Caffe.
• Familiarity with AWS or any cloud based compute offerings
• Excellent verbal and written communications skills.
• Ability to work independently, without direct supervision.
Universal Robotics creates Artificial Intelligence that uses sensor data to update control system behavior in real time. The technology was developed at NASA and Vanderbilt University. Called Neocortex, Universal is implementing the technology on industrial robots and other hardware to improve automation and human/machine interaction. Most of the technical staff have advanced degrees (PhD, MS), and are experts in robotics, vision, machine learning, artificial intelligence, and 3D sensor technologies.