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Scandit is a high-growth tech scaleup from Switzerland with offices in Zurich, Boston, Warsaw, London, Singapore, Tokyo, and Tampere. Our market-leading smart data capture technology enables businesses to use any standard mobile phone to extract data from barcodes, ID documents, text, and objects. To see our software in action, check out our videos. The barcode decoding team at Scandit builds cutting edge decoding solutions. Our mission is to replace every laser scanner in the world with a Scandit powered mobile app.

Scandit is a high-growth tech scaleup from Switzerland with offices in Zurich, Boston, Warsaw, London and Tampere. Our technology for recognizing any barcode with any standard mobile phone is leading in the market today. To see our software in action, check out our videos. We are now looking for a new colleague to join our passionate team of computer vision engineers and help us make the next steps. Together with the other team members, you will be responsible for further improving our scanning performance and making it work in even more challenging conditions by applying and optimizing computer vision and deep learning algorithms.

At Scandit, we develop real-time computer vision solutions for smartphones, wearables and robots that combine modern machine learning approaches with computer vision. To expand our engineering team, we are looking for an engineer who is passionate about machine learning and has a solid track record in it, to work on deep learning applications for our computer vision pipelines. As a part of our growing team in Tampere, you will be working with image processing and computer vision specialists to develop algorithms for real-time barcode decoding, text recognition and object detection for robust real-world performance. The solutions you develop will be running on hundreds of millions of mobile devices on which our real-time computer vision products are deployed today. Scandit enables enterprises and consumers to change the way they interact with everyday objects and augment the physical world with real-time data captured by scanning barcodes and recognizing text, objects, and other visual identifiers using smartphones, tablets, wearables, drones and robots.

Did you miss a session from GamesBeat's latest event? Inventory management is a growing challenge in retail and logistics, particularly as the pandemic places a strain on the supply chain. According to a 2018 survey by Coresight Research and Celect, inventory decisions -- including overbuying, buying the wrong type of products, and misallocating inventory -- account for an estimated 53% of unplanned markdown costs for retailers. Similarly, a Stitch Labs survey of warehouse operators found that human error was the top cause of inventory fulfillment issues for a majority of the respondents. Some problems stem from the barcode- and label-based systems that companies use to keep track of products, which can be susceptible to incorrect data, poor print quality, and other inconsistencies. Automation technologies have been proposed as a solution in light of the growing trend toward digitization in logistics.