Luxoft, a DXC Technology Company, (NYSE: DXC), is a digital strategy and software engineering firm providing bespoke technology solutions that drive business change for customers the world over. Luxoft uses technology to enable business transformation, enhance customer experiences, and boost operational efficiency through its strategy, consulting, and engineering services. Luxoft combines a unique blend of engineering excellence and deep industry expertise, specializing in automotive, financial services, travel and hospitality, healthcare, life sciences, media and telecommunications. For more information, please visit

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Senior/Principal Deep Learning Engineer for Automotive Project, Krakow

Project Description

An autonomous car startup on a mission to make cities safer and more efficient with better drivers. We're looking for engineering and business professionals who love to design, build and scale real-time distributed systems to join our growing team in Palo Alto.

Merging artificial intelligence with computer vision, client's systems detect and react to what's happening on the road ahead of a driver and within the vehicle. The algorithms sense when there is an issue on the road ahead, or a distraction within the vehicle, and helps the driver respond. They also automatically understand when a collision is about to happen, and record the scene inside and outside of the car then. Images and data about the incident are stored in the cloud, and can be shared via client's app and fleet management tools.
The company's systems are already running on several classes of high-volume commercial vehicles. Longer term, client will continue to partner with auto manufacturers to evolve its systems from an onboard safety AI into a platform that accelerates the development of autonomous vehicles.


• Designing, training and deploying neural networks for complex computer vision problems
• Keeping up with recent AI research results and implementing/improving on winning DNN algorithms



• M.Sc. or Ph.D. in Computer Science, Math, Physics or similarly quantitative-heavy background
• Experience with implementing DNNs for computer vision problems such as object classification, object detection and localization, semantic segmentation
• Experience with deep learning frameworks such as Caffe, Theano, Torch, Keras or Tensorflow
• Familiarity with OpenCV or other computer vision libraries
• Experience with traditional computer vision methods is a bonus
• Knowledge and experience in Machine Learning at least 3 years
• Proficiency in C/C++, Python, Unix/Linux scripting

Nice to have

Working in automotive projects


  • English: Intermediate

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