Responsibilities

The successful candidates will be knowledgeable and innovative engineers who take pride in solving challenging problems. Responsibilities include:

• Solve real-world problems using your machine learning skills
• Participate in cutting-edge research for computer vision applications.
• Drive end-end machine learning developments from use-case analysis to data curation, training and optimization
• Develop and implement video and image processing methods
• Work on models that will push the current state of computer vision/machine learning
• Optimize models to fit within resource constrained embedded systems

Qualifications

• 8+ years experience solving problems using ML
• Experience with at least one deep-learning environment such as Caffe, TensorFlow, Tensorflow Lite or Keras
• Proven success in full-cycle ML development, from data gathering through training and optimization
• Strong theoretical and practical understanding of deep-learning, Convolutional Neural Networks (CNN)
• Experience with ML optimization techniques, for example quantization, pruning, and distillation

Preferred

• Experience in implementing object detection/classification including traditional handcraft feature-based methods in the image processing domain ((HOG, SIFT, Gabor filter, etc.).
• Experience with machine vision libraries for software development, such as OpenCV
• C/C++ and Python coding and debugging skills, familiarity with multi-threaded programming