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We have an exciting opportunity to join our team servicing the Group Risk division of a leading bank. If you have a passion for Gen AI and have strong experience in working with NLP models and chatbots, you might be the person we are looking for.
Utilise technical knowledge of, and experience in, the following to address AI and ML solution requirements – ML Concepts; Software Engineering Discipline ; major ML frameworks ; Big Data Processing Libraries ; structured and unstructured data; building end-to-end solutions on Cloud ; working with and tuning pre-built AI Services in Cloud; Data Visualisation software . Deliver technical artefacts articulating the architecture and model robustness of AI solutions, supporting the development of Technical Documentation within the area. Develop web applications using Python frameworks to enable business to interact with Machine Learning models. Provide automation support for ML pipelines; build code, run tests , and safely deploy a new version of an application to allow for the removal of manual errors, and provide standardised feedback loops, to enable fast product iterations. Apply new techniques and technologies to business problems and solve them in new and creative ways in order to provide greater insight, accuracy and consistency. Investigate and implement latest large language models to mature the Virtual risk manager : enable the virtual risk manager to be used as a channel to deliver risk solutions. Work with business stakeholders to identify new AI initiatives. Perform rapid EDA / prototyping exercises to help size projects and high-level success criteria, meeting the project pipelining requirements of the role.Present relevant content at architecture, technical committees and business stakeholders Produce Solution Designs and Architecture for review / vetting, and reusable solution patterns for use in other projects, supporting the enablement of other team members. Discuss needs with the user and collaborate with the wider team to contribute to the development of a solution that is user-centric and aligned to business goals, ensuring that the solution is fit-for-purpose. Conduct research into and carry out AI and ML development processes to ensure the business unit fulfils the needs of AI and ML strategies. Convert conceptual AI needs into crystalized problem statements that can be scientifically measured to support these needs. Apply engineering and math skills to analyse and prepare structured/unstructured data for modelling, to support the Data Analysis and Engineering requirements of the role. Apply the most appropriate algorithms and/or build novel algorithms/techniques to fit the problem statement identified, which will support AI Modelling; take advantage of pre-built AI capabilities offered by Cloud vendors where appropriate to increase project velocity, take advantage of latest start-of-the-art commercialized AI solutions and reduce internal technical debt. Incorporate AI models into software that meets the upstream or downstream system requirements , supporting the solutioning of the team.
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