Machine Learning Engineer - London

London, UK /
London, UK – Data Science - London /
Full-time is at the forefront of revolutionizing healthcare for millions of patients worldwide. Combining more than 20 years of proprietary wearable technology with clinically relevant signals, connects patients and physicians like never before with continuous, data-driven dialogue. This unique position of daily directed guidance stands to redefine primary care, while helping people live happier, healthier and longer.

You will be joining a data science team in London and be in a unique position to help shape the team and projects we will be working on, as well as the tools and techniques we will be adopting. If you are a self-starter and mathematical modeling is your utmost interest then this might be the right position for you. 

* This position is listed for London, however with the current pandemic environment, it will start as a remote position within the UK.


    • Deep understanding of probability and statistical theories 
    • Strong programming skills in python including the python data science stack (pandas, numpy, scipy, sklearn, etc)
    • Specialised in various machine learning techniques such as support vector machine, ensemble methods (i.e. random forest) and their implementation using python libraries.  
    • Hands-on experience of data transformation, feature extraction and selection, dimensionality reduction, model construction, model validation, etc. 
    • Experience with statistical error estimation techniques such as cross-validation and bootstrapping
    • Experience developing and implementing predictive models in a product development environment
    • M.Sc (or PhD) in machine learning, statistics, electrical engineering, physics or computer science from top universities
    • High intellect and ability to solve extremely challenging predictive modeling problems applied to a variety of different domains
    • Ability to work independently with minimal supervision


    • Bayesian statistics and graphical model
    • Background in digital signal processing, image detection or NLP (word2vec, node2vec) 
    • Understanding of the issues & challenges with deep neural networks such as interpretation of neuron functions, hyperparameter tuning for architectural design, evaluation of overfitting and generalization, various regularization and optimisation techniques, etc
    • 2-3 years work experience applying machine learning techniques to real business problems