The world's leading retailers trust and rely on Everseen's Visual AI™ solutions to improve their bottom line by minimizing shrink, streamlining operations via hyper automation, and delivering a better customer experience.
Everseen’s Visual AI™ is a comprehensive process aware platform that delivers Checkout Intelligence, Shelf Intelligence, Supply Chain Intelligence, Car Lot Intelligence, Production Line Intelligence, and Generic Process Automation Applications, transforming how businesses see and solve their most costly problems. The company’s ground-breaking AI technology processes over 200 years of video footage every day and protects ~$500B worth of assets.
Everseen has earned multiple industry accolades, including 5 consecutive years as Gartner’s Top Pick for Retail Technology Innovation, Deloitte’s Tech Fast 50 winner, and Google & Deloitte’s new Tech award winner. Everseen is headquartered in Ireland, with its US Head office in Miami as well as R&D Centres in Timisoara, Romania; Belgrade, Serbia; and Barcelona, Spain. For more information visit www.everseen.com.
This position will be part of our Machine Learning - Computer Vision Research team that has generated 4th Generation of Everseen ML products which is deployed in thousands of stores worldwide.
Reading scientific papers and implementing appropriate solutions and adjusting the cuttingedge solutions to project needs
Developing novel solutions in computer vision for retail
Proposing improvements of existing solutions
Building/optimizing deep learning-based models for extraction of useful knowledge from real-time video streams.
Presenting results using data visualization techniques
Successful candidature requirements
MS or Ph.D. in computer science, electrical engineering, mathematics/statistics, other relevant technical university, or enthusiasts with a strong background / high level of experience in the before mentioned domains.
The applicants should have intermediate skills in software engineering with expertise in at least one programming language (e.g. Python – preferable, C++, Java…).
A suitable candidate should be familiar with some of computer vision, machine learning and deep learning libraries (e.g. OpenCV, TensorFlow, Caffe, Keras, PyTorch, Scikit-learn…).
The applicants should have deep understanding of machine learning concepts from both theoretical and practical perspectives.
Academic connection is part of our essence, so we would embrace experienced lecturers, teachers / professors who want to take part in this endeavor. Still, programming skills are a must for all members of the team as we see this as one of the critical links between them.
The candidate must be a highly creative out-of-the-box problem solver, capable of proposing novel solutions to problems, performing experiments to show feasibility of their solutions, and working to refine the solutions into a real-world context.
Strong written and verbal communication skills (English)
Other Candidate relevant aspects
Preference will be given to individuals: with demonstrated / industrial research in the fields of machine learning and deep learning with special focus on computer vision.
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