Senior Computer Vision R&D Engineer

About Pretia Technologies

We believe in the tremendous power of bringing people together beyond devices. Sharing time together in the real-world, working towards a goal with people you care about is the key to leading a happy, fulfilling life.

With the rise of AR technology, we envision a world where any physical location becomes a space for all kinds of shared experiences. Allowing people to collaborate and enjoy a sense of achievement at any time, any place, with anyone.

Position

• Pretia Technologies is looking for a world-class computer vision researcher with extensive experience in SLAM to solve the most challenging and cutting-edge problems in the field of AR
• You will be required to design and implement advanced algorithms for large-scale localization and mapping, combining challenging academic work with the real-world impact

Your qualification

• 3+ years software engineering experience in computer vision or machine learning
• Experience with computer vision (SLAM, feature and object detection/ recognition/ tracking etc.)
• Experience with machine learning, deep neural networks, frameworks (e.g. Caffe, TensorFlow, Theano, Torch etc.) 
• Proficiency in C++ skills

Will be a plus

• Experience with C#, RESTful API, android, iOS 
• Experience with Android native app development 
• Experience with Java
  • Sharing our mission and values
  • Always striving for excellence in execution
  • Strongly interested in AR technology and excited about its future
  • Kind and sincere
  • Willing to communicate in English
  • Like to make others happy
  • Can agree with not being given any title and working as a member at the beginning

What we offer

• Transportation: 100% covered
• Health and social insurances: available
• Visa sponsorship: available
• Latest AR/VR hardware installed in the office
• Opportunities to experience the new entertainment crazes are frequently provided
• International working environment in a calm part of the city
• The rare opportunity to be involved in learning nearly every aspect of how an early-stage startup grows and scales