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Harnham
,
London, Greater London
Machine Learning Engineer
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Job Type: Full-time |
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Salary: £60,000 per annum |
Overview
MACHINE LEARNING ENGINEER UP TO £65,000 10% BONUS BENEFITS PICADILLY, LONDON Are you excited by the opportunity to work for a well-established, data-driven gaming company with the goal of making intelligent decisions for their players? Do you think outside the box when thinking of ways that machine learning techniques can benefit and optimise business performance? This an exciting new challenge for an experienced Machine Learning Engineer. THE COMPANY: As a Machine Learning Engineer, you will work in a fast-expanding department for a well-established gaming company that has been around for nearly 20 years. You will work in a variety of different business areas for a company that genuinely values employee input and needs. THE ROLE: The role of Machine Learning Engineer will involve working on a variety of different projects around online and mobile gaming Specifically, you can expect to be involved in the following: You will be building end-to-end machine learning models in Python You will be using deep learning, NLP and different machine learning techniques in different projects related to marketing, finance, customer and gaming analytics You will have a big involvement in conceptualising the machine learning models until deployment You will be communicating with stakeholders and making new products You will be doing projects in reinforcement learning YOUR SKILLS AND EXPERIENCE: The successful Machine Learning Engineer will have the following skills and experience: Educated to degree level in quantitative methods and statistics (Science, Technology, Engineering, Mathematics etc) Proficiency in programming languages and statistical analysis tools - Python, numpy, GCP, AWS Previous experience commercial experience building machine learning models to gain business insights THE BENEFITS: The successful Machine Learning Engineer will receive a salary, dependent on experience of up to £65,000. HOW TO APPLY: Please register your interest by sending your CV to Francesca Curtis via the Apply link on this page.