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Sr. Deep Learning Engineer

At Bossa Nova we create service robots for the global retail industry. Our robots’ mission is to make stores run efficiently by automating the collection and analysis of on-shelves inventory data in large scale stores. Navigating smoothly along the aisles, we circulate autonomously among busy customers and employees. If we were a self- driving car we’d be operating at level 5 autonomy.  Yep, it is possible to move, scan and analyze all at the same time. It is not that simple though and we rely on computer vision, 3D image processing and deep learning techniques to accomplish our mission.

Oh, we should add, it’s real, happening today, you can meet our robots in some of the world’s biggest retailers or follow us on Instagram @bnrobotics

You are passionate about technology, you strive in a fast-pace environment? We probably have something to interest you. We are hiring!

Position: Principal Data Scientist- Deep Learning

Location: San Francisco or Pittsburgh

We are looking for an experienced Senior Deep Learning Scientist with computer vision background to work on analysing and understanding what the robot sees and converting that into business values for the company and customers.


  • Architect, develop, train and productize deep learning solutions for image analysis including object detection, object recognition, scene understanding and semantic segmentation
  • Develop deep learning systems that can be robust and can scale across variations in data and complex use cases


  • MS or PhD in Computer Vision, Computer Science, Data Science, Machine Learning, or related field
  • 2+ years of production level experience in developing deep learning algorithms and technologies for solving computer vision problems
  • Experience with at least one major deep learning framework (TensorFlow, Caffe, Theano, Torch, CNTK, MxNet). Experience with TensorFlow preferred
  • Strong knowledge of deep learning theory (CNNs, RNNs, LSTMs, etc.)
  • Strong C++, Python skills
  • Strong problem solving skills and ability to learn quickly
  • Being up-to-date on trends and developments in deep learning

Nice to Have:

  • Experience deploying and scaling deep learning models in Cloud (Azure in particular)
  • Experience optimizing the DL models to run faster during inference time
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