An early stage food tech company which uses deep learning-based computer vision, causal inference, and cognitive AI to change how we feed the people around the world. They are starting by providing software services to existing restaurant chains which use the live camera feed to provide augmentation for staff tasks with aim to help decision making, reduce error and cognitive load needed. Their mission is to feed the world through a global food system which is more productive, resilient, more affordable, more sustainable, and healthier. A food system that provides accessible nutrition for everyone while preserving our planet. The team includes people with extensive experience on the creation and deployment of scalable deep tech solutions as well as industry experts who share a passion for food, happiness and our world. That is where you come in.
Responsibilities Include
Solve research and clients’ challenges in the field of computer vision using deep learning methods.
Implement and modify machine learning methods using best software development practices.
Train, analyse and report model performance.
Develop tools for further automating research and analysis.
The role involves pushing the boundaries of what deep learning can do, by following and building upon the latest research in the context of object detection, classification and semantic segmentation.
You will be joining an early-stage startup with the ability to shape our future direction both for our research and for the solutions we deliver to customers.
Requirements
3+ years (required) 5+ years (desired) experience of applying machine learning and deep learning methods in the industry.
Experience in developing practical deep learning applications using detection architectures (Faster-RCNN, SSD, YOLO, EfficientDet)
Solid theoretical understanding of machine learning and neural networks
Experience with machine learning methods, such as active learning, clustering, semi-supervised learning, zero- and few-shot learning
Solid hands-on software development skills in Python (numpy, scipy, scikit-learn, OpenCV) and familiarity with C++
Ability to write clear, efficient and scalable code
Experience with one or more Deep Learning Framework (Pytorch, Tensorflow)
