Experienced Computer Vision/Deep Learning Engineer Computer Vision, Remote, Full-Time
Are you interested in joining a talented team of developers working remotely on pushing the boundaries forward for autonomous technologies?
We want someone who can think outside the box, who is energetic and passionate about their work. You will be working alongside a diverse group in a fast paced environment. Your will be researching new learning techniques based in existing papers, generating synthetic datasets for our clients to improve their neural network models and producing empirical studies. Our clients come from various sectors including autonomous vehicle, government, robotic farming, industrial automation, etc.
You are not expected to have mastery of deep learning — the problems we pursue are always at the edge of the state of the art, which means that nobody's an expert.
- Using our simulator you will generate synthetic environments and sensor modelling for the purpose of developing and testing object detection, classification algorithms and deep learning in general for several applications, including automation, unmanned/autonomous ground, air, marine applications. (80%)
- Document algorithmic approaches, test results, prepare scientific technical reports, present results, and demonstrate system capabilities to internal team, clients and partners. (20%)
M.S. in Computer Science, Computer Vision and/or Machine Learning development experience. Experience in working with Python, C/C++. Able to work independently and with a team, possess excellent written and oral skills.
Prior experience developing software for unmanned platforms. Additionally, exposure to any or all of the following technologies is beneficial: CUDA, GPGPU computing, Caffe, Tensorflow, MATLAB, Boost C++ libraries. Familiarity with embedded programming principles and algorithm optimization for resource-constrained platforms.
The ideal candidate will possess initiative, creativity, breadth of knowledge and a desire for continuous learning.
Remotely from home, beach or anywhere that has an internet connection. This is a full-time position.Send CV