<p dir="ltr">We are looking for a Machine Learning engineer with experience in Computer Vision to join our team. You’ll play an important role in designing the neural networks that power the core of our technology, while also owning an important part of the ML stack.<br></p><p dir="ltr"><strong>Key Qualifications:</strong><br></p><ul><li dir="ltr"><p dir="ltr">Master's degree or equivalent level of experience in Computer Science, Electrical Engineering, Computer Vision, Machine Learning, or a related field.</p></li><li dir="ltr"><p dir="ltr">Minimum 2 years of hands-on experience with neural networks, both designing and deploying them on various hardware platforms. </p></li><li dir="ltr"><p dir="ltr">Understanding of computer vision algorithms, machine learning, and software development.</p></li><li dir="ltr"><p dir="ltr">Proficiency in programming in Python, with knowledge of different Deep Learning frameworks (TensorFlow, PyTorch, Keras etc.) and OpenCV. Some knowledge of C++ is a plus.</p></li><li dir="ltr"><p dir="ltr">Basic knowledge of the MLOps stack, and basic understanding of data engineering.</p></li><li dir="ltr"><p dir="ltr">Experience with Cloud Platform, especially GCP is a plus. </p></li><li dir="ltr"><p dir="ltr">Strong problem-solving skills and the ability to work in a collaborative team environment.</p></li><li dir="ltr"><p dir="ltr">Excellent communication skills in English.</p></li><li dir="ltr"><p dir="ltr">Experience in Agile software development.</p></li></ul><p dir="ltr"><strong>Responsibilities:</strong></p><p dir="ltr"> </p><ul><li dir="ltr"><p dir="ltr">Design neural networks for Computer Vision applications, with a focus on latency and low-computational power systems.</p></li><li dir="ltr"><p dir="ltr">Design and maintain MLOps pipelines to manage experiments, guaranteeing their reproducibility. </p></li><li dir="ltr"><p dir="ltr">Taking a part in designing and running efficient large data pipelines that feed into our training infrastructure.</p></li><li dir="ltr"><p dir="ltr">Stay updated on the latest advancements in machine learning and apply them to our technology. </p></li></ul> •
Last updated on Sep 12, 2024