PwC has an exciting opportunity for an AI / GenAI Engineer who has extensive working experience within the Retail Banking space. This role will give the successful incumbent an opportunity to work on innovative projects while leveraging new and advanced technologies to drive transformative solutions. The successful incumbent will have a strong background in artificial intelligence and machine learning, with a focus on developing and deploying generative AI models. You will work on cutting edge projects that involve designing, building, and maintaining AI solutions to solve complex problems.Qualifications Bachelor's degree in computer science, Engineering, Data Science or a related fieldRelevant certifications in AI/ML or related fields are highly advantageousExperienceMinimum 4 years working experience in AI/ML engineering or related rolesProven work experience in developing and deploying AI/GenAI modelsRelevant working experience in Retail BankingStrong understanding of machine learning, deep training, and generative AI techniquesProficiency in programming languages such as Python, R, and JavaExperience with AI/ML frameworks and libraries (TensorFlow, PyTorch, Keras)Solid experience developing and implementing generative AI models and algorithms utilising techniques such as GPT, VAE and GANs.Knowledge of natural language processing (NLP), computer version, and other AI application areasExperience with data preprocessing, feature engineering, and model evaluation. Familiarity with cloud platforms and services (AWS, Azure, Google Cloud)Excellent analytical and problem solving abilitiesStrong communication and collaboration skillsAbility to work independently and as part of a teamResponsibilities:Model Development:Design, develop, and deploy advanced AI and generative AI modelsConduct research to improve existing models and create new algorithmsData management:Collect, preprocess, and analyse large datasets to train AI modelsEnsure quality data, consistency, and integrity throughout the development process. Solution implementation:Implement AI models into production systems, ensuring scalability and performance. Collaborate with software engineers to integrate AI solutions with existing applicationsPerformance Monitoring and Optimisation:Monitor the performance of AI models and make necessary adjustments to improve accuracy and efficiency.Conduct experiments and A/B tests to validate model improvement. Collaboration and Communication:Work closely with cross-functional teams, including data scientists, project managers, and software engineers, to deliver AI-driven solutionsPresent findings, insights, and recommendations to stakeholders in a clear and concise mannerInnovation and Research:Stay updated with the latest advancements in AI and generative AI technologies. Participate in research projects and contribute to the development of innovative solutions.
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