Machine Learning Engineer - Nederland - Realfacevalue

Realfacevalue Nederland

1 week geleden

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Working at realfacevalue

Machine Learning Engineer As a Machine Learning (ML) Engineer at Real Face Value, you will be part of a dynamic, growing team with a startup atmosphere.

RealFaceValue 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. See more on or and socials.

Working with us

As a Machine Learning (ML) Engineer at Real Face Value, you will be part of a dynamic, growing team with a startup atmosphere. If you have a passion for creating innovative solutions and want to be part of a cutting-edge technology company, we encourage you to apply. Real Face Value offers a competitive salary and vacation days, flexible working hours (0.6fte part-time to full-time), and flexible remote working conditions.

RealFaceValue is seeking a junior or medior ML engineer to join our team. As a ML engineer developer, you will work on development and deployment of predictive and generative computer vision models. Specifically, you will do research and development on facial trait estimation and semantic face editing using deep neural networks. You will be working directly with the tech lead of RFV.

Responsibilities

Processing, cleansing, and verifying the integrity of data used for analysis
Prototyping, evaluation, and comparison of trait estimation models
Developing novel methodologies for semantic face editing with generative models
Doing ad-hoc analysis and presenting results in a clear manner
Supervising the deployment of machine learning models
Pre and post-processing images with image processing techniques such as masking, morphology, alignment, warping and composition.

Required skills

Excellent understanding of machine learning and computer vision techniques and algorithms
Good knowledge of Python and programming skills
Experience with common data science toolkits such as NumPy, SciPy, and scikit-learn
Experience with deep learning frameworks such as PyTorch
Bachelor'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 learning

Preferred skills

Experience with state-of-the-art Generative Adversarial Networks such as StyleGAN2 and 3
Experience 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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