We are seeking a talented Computer Vision Researcher to join our team. As a Computer Vision Expert, you will have the following responsibilities and challenges: Research: Study and apply classical computer vision and optimization algorithms to improve system components Develop: Create reliable and efficient Machine Learning models for object detection, segmentation, and classification Design: Devise intelligent methods for building relevant and qualitative datasets Solve: Apply state-of-the-art methods to address unique challenges in the wood industry Scale: Enhance the scalability of ML solutions Innovate: Develop accurate and efficient 3D modeling techniques using stereo vision, structured light, and ML We work in small teams with a startup mentality. We are a horizontal organization where originality and self-drive are valuable assets that we encourage. Our team members have diverse research and technical backgrounds in various complementary fields. You will have a key position in designing and building innovative products. Our clients are the largest lumber sawmills worldwide. These companies play a key role in the transition to a carbon-neutral world, and we help them bring innovation, technology, and automation to drive efficiency and reduce waste. A typical candidate would have experience in Classical Computer Vision and Machine Learning have experience working with large datasets draw data-driven conclusions using statistical inference have programming experience in Python and Java have hands-on experience with Tensorflow or PyTorch be self-driven and able to independently carry a task to completion be pragmatic and goal-oriented The ideal candidate would have a PhD in a STEM field or 3-year experience in a research position in the industry have an advanced understanding of deep learning techniques applied to computer vision problems enjoy reading the latest academic papers in the field have implemented computer vision algorithms in an industrial setting (wood industry would be perfect) thrive in a client-driven research environment that requires perseverance and creative solutions Benefits training, knowledge