Requirements:
• Master of Science in Computer Science, Statistics, Operations Research, Applied Mathematics, and Engineering.
• At least 2 years of professional post-graduate experience in applying MLOps best practices on a productive Machine Learning system.
• Professional experience in developing algorithms and solving problems in the field of computer vision and image processing and experience with deep learning libraries such as TensorFlow, Keras, PyTorch, etc.
• Practical and proven expertise in at least 2 of the following areas: Computer Vision, Object Detection, Un/Semi/Supervised Machine Learning and Deep Learning, Convolutional Neural Networks, Reinforcement Learning, GANs, Out-of-Distribution (OOD), Active Learning and (Vision) Transformers.
Or Practical and proven expertise in at least 2 of the following areas: Un/Semi/ Supervised Machine Learning and Deep Learning, Audio Source Separation, Speech Separation, Voice Activity Detection, Automatic Speech Recognition and Transformers.
• Practical experience in data engineering and cloud computing (AWS, GCP, MS Azure).
• Ability to read, understand and implement research papers.