We are looking for a Site Reliability Engineer to help us deploy our algorithms in retail stores. Our focus is on efficient, easy-to-scale, easy-to-maintain on-premise deployments.
-Automate the server provisioning process.
-Research the most efficient solution for integration (Jetson, FPGA, GPU server).
-Plug the solution to local Digital Video Recorder (DVR) or directly to IP cameras.
-Develop tooling to monitor systems and diagnose performance bottlenecks.
-Eliminate inefficiencies and simplify our build process.
-Linux (incl. Bash).
-Databases (preferably PostgreSQL or similar).
-Experience with one or more of these languages: Python, Go, Java, C/C++, C#.
-Experience with OpenCV is a big plus.
-Experience in video network setup.
-Configuring and maintaining secure network architecture.
-Knowledge of resource management and job scheduling tools (SLURM, SGE, etc.)
 Bolei Zhou, Alex Andonian, Antonio Torralba : Temporal Relational Reasoning in Videos arXiv:1711.08496
 Jiawei He, Mostafa S. Ibrahim, Zhiwei Deng, Greg Mori : Generic Tubelet Proposals for Action Localization arXiv:1705.10861
 Sijie Yan, Yuanjun Xiong, Dahua Lin : Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition arXiv:1801.07455
 Max Jaderberg, Karen Simonyan, Andrew Zisserman, Koray Kavukcuoglu : Spatial Transformer Networks arXiv:1506.02025
 Zhenzhong Lan, Yi Zhu, Alexander G. Hauptmann : Deep Local Video Feature for Action Recognition arXiv:1701.07368
 Eddy Ilg, Nikolaus Mayer, Tonmoy Saikia, Margret Keuper, Alexey Dosovitskiy, Thomas Brox : FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks arXiv:1612.01925
 Thomas Schlegl, Philipp Seeböck, Sebastian M. Waldstein, Ursula Schmidt-Erfurth, Georg Langs : Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery arXiv:1703.05921
Paris – Full time
€40k – €60k
Founded by Polytechnique and HEC alumni, Veesion is incubated at Agoranov (96 bis Boulevard Raspail, 75006 Paris).
We are developing a gesture recognition technology in video content. The potential applications are diverse and our first focus is shoplifting detection in the retail industry.
We built a large video database thanks to partnerships with major retailers and we are in constant discussion with top-notch Computer Vision labs such as the Thoth and Willow teams in order to drive our research.
We are a young and agile startup: joining us now is the opportunity to grow with the company.