Machine Learning Engineer

June 20

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Ripjar

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Data Intelligence

Financial Crime • Data Fusion • Automated Analytics • Data Intelligence • Natural Language Processing

51 - 200

Description

• At Ripjar, you will design and implement machine learning solutions, develop and optimise their models, and ensure their integration into Ripjar's software products and data processing pipelines, focusing on enhancing system performance and scalability. • Develop architectures and frameworks for machine learning systems that can handle large-scale data and complex computations. • Develop and evaluate machine learning models to enhance Ripjar’s software and data products. • Integrate ML models into new and existing components and consider the lifecycle and practical use of each model. • Implement feature requests for Ripjar’s analytics components. • Work with Ripjar's Data Engineers and engineering teams to support the scaling up and integration of new analytics and models into Ripjar's products and data processing pipelines. • Produce statistical tests and summarise test outputs. • Document system designs, models and test methodologies. • Provide support to stakeholders in understanding the implementation of analytics, models and test results. • Make use of Ripar’s large-scale data processing and analysis infrastructure to analyse data sets in order to identify patterns and to produce statistical outputs to support the development of new analytics and models.

Requirements

• A good understanding of machine learning and experience training and deploying machine learning models within products at scale, including ongoing maintenance. • Proficiency using a range of machine learning techniques including Natural Language Processing techniques for solving problems, and ideally making use of Large Language Models • Proficiency in Python, particularly with machine learning and data science libraries such as PyTorch/Tensorflow, scikit-learn, numpy and pandas. • Good communication and interpersonal skills. • Experience working with large-scale data processing systems such as Spark and Hadoop. • Experience in software development in agile environments and be an advocate of the software development lifecycle. • Experience using and implementing ML Operations approaches • Working knowledge of statistics and statistical models is valuable.

Benefits

• Base Salary of up to £70,000 per year DOE • 25 days annual leave, rising to 30 days after 5 years of service • Hybrid working option for employees • Company Share Scheme • Private Family Healthcare • Employee Assistance Programme • Company contributions to your pension • Enhanced maternity/paternity pay • The latest tech including a top of the range MacBook Pro • Candidates can work from our Cheltenham, Bristol or London offices • Offices equipped with well-stocked pantries with food, snacks and drinks when in the office