About the position
In summary:
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.
Expanded Responsibilities:
- Utilise technical knowledge of, and experience in, the following to address AI and ML solution requirements - ML Concepts; Software Engineering Discipline (e.g. Source Control, CI/CD); major ML frameworks (TensorFlow, PyTorch, scikit-learn); Big Data Processing Libraries (e.g. Spark, Dask); structured and unstructured data; building end-to-end solutions on Cloud (Azure); working with and tuning pre-built AI Services in Cloud; Data Visualisation software (Power BI etc.).
- 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 (CI), and safely deploy a new version of an application (CD) 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 (Chatbots): 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.
- Work with internal clients to shape new AI projects, meeting client needs as identified.
- 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 (non-technical) 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 (i.e., Engineering Batch, Streaming or API based ML pipelines), supporting the solutioning of the team.
Desired Skills:
- Gen AI
- NLP
- RAG
- Predictive modelling
- Data Science
- Applied mathematics
Desired Work Experience:
Desired Qualification Level:
About The Employer:
Leading SA bank
