Description Revolutionize technology application in real-world scenarios, promoting impactful change and innovation. As an Applied AI/ML Associate within our dynamic team of innovators and technologists, you will revolutionize how the Private Bank services and advises clients, deepen client engagements, and promote process transformation. You will analyze existing processes and vast amounts of data to design autonomous AI agents, leveraging advanced data analysis, statistical modeling, and AI/ML techniques to solve complex business challenges through high-quality, cloud-centric software delivery. J ob Responsibilities Develop and implement GenAI and Agentic AI solutions using Python to enhance automation and decision-making processes. Collaborate with internal stakeholders to identify business needs and develop NLP/ML solutions that address client needs and drive transformation. Apply large language models (LLMs), machine learning (ML) techniques, and statistical analysis to enhance informed decision-making and improve workflow efficiency, which can be utilized across investment functions, client services, and operational process. Collect and curate datasets for model training and evaluation. Perform experiments using different model architectures and hyperparameters, determine appropriate objective functions and evaluation metrics, and run statistical analysis of results. Monitor and improve model performance through feedback and active learning. Collaborate with technology teams to deploy and scale the developed models in production. Deliver written, visual, and oral presentation of modeling results to business and technical stakeholders. Stay up-to-date with the latest research in LLM, ML and data science. Identify and leverage emerging techniques to drive ongoing enhancement. Required qualifications, capabilities and skills • Develop and implement GenAI and Agentic AI solutions using Python to enhance automation and decision-making processes. • Develop and maintain machine learning models to solve complex business problems • Collaborate with cross functional teams to identify opportunities for leveraging data to drive business solutions • Analyse large, heterogenous datasets to extract actionable insights and inform decision-making • Stay updated with the latest advancements in machine learning and especially Large Language Models and agentic systems • Identify the right state of the art solutions for the bank’s objectives and implement them as clean, production-ready code • Communicate findings and recommendations through clear and concise reports and presentations • Required qualifications, capabilities and skills • Proficiency in Python and SQL and familiarity with good software engineering practices • Excellent written and verbal communication • Strong experience developing, testing machine learning solutions using frameworks such as TensorFlow, PyTorch or scikit-learn • Solid intuitive grasp of fundamental concepts from probability, statistics, linear algebra and calculus • Collaborative, humble and enthusiastic attitude Preferred qualifications, capabilities and skills • Experience deploying on AWS cloud infrastructure using Lambda, Glue, S3 etc • Experience in deep neural networks and familiarity with the latest developments in related fields • Experience in LLM model finetuning and continuous learning techniques • Experience in prompt engineering techniques and state-of-the-art LLM architectures