Machine Learning Engineer (Closed) Flexible remote

As a Machine Learning (ML) Engineer at Real Face Value, you will be part of a dynamic, growing team with a startup atmosphere.About RealFaceValueRealFaceValue is a company positioned at the intersection of artificial intelligence and human intuition. Based on extensive behavioural scientific research, 20+ years of facial congenital and aesthetic treatment experience, machine learning expertise, and vast amounts of data, we created a solution that works as a socio-economic compass of how others perceive you in today's society. We focus on how you look, more specifically how your face is perceived and what can actually be achieved, and by which treatment while staying within the boundaries of natural appearance. We are active in multiple markets with a focus on health and beauty. Real Face Value received a considerable amount of seed funding and we are ready to expand the team to 5-10 people. We work from Rotterdam, Amsterdam and Den Haag; working remotely partially is possible.Working with usReal Face Value offers a competitive salary and vacation days, flexible working hours (0.6fte part-time to full-time), and flexible remote working conditions.ResponsibilitiesProcessing, cleansing, and verifying the integrity of data used for analysisPrototyping, evaluation, and comparison of trait estimation modelsDeveloping novel methodologies for semantic face editing with generative modelsDoing ad-hoc analysis and presenting results in a clear mannerSupervising the deployment of machine learning modelsPre and post-processing images with image processing techniques such as masking, morphology, alignment, warping and composition.Required skillsExcellent understanding of machine learning and computer vision techniques and algorithmsGood knowledge of Python and programming skillsExperience with common data science toolkits such as NumPy, SciPy, and scikit-learnExperience with deep learning frameworks such as PyTorchBachelor's and/or Master's degree (can be ongoing) in one of the following branches: Computer Science, Mathematics, Statistics, Electrical Engineering; preferably with a focus on A.I. and machine learningPreferred skillsExperience with state-of-the-art Generative Adversarial Networks such as StyleGAN2 and 3Experience with deep learning architectures widely used in CV such as ResNet, VGG, etc.Experience with image processing-computer vision libraries such as OpenCV, PIL, skimage etc.Experience with face recognition systems such as OpenFace, FaceNet, etc.Experience in taking machine learning models to production, and then maintaining and monitoring them.Experience in model deployment in Amazon Web Services (AWS)

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