YOU WILL NEED:

• Ideally 7+ years of experience in machine learning and AI, with a significant portion dedicated to generative AI techniques
• Proven track record of deploying transformer-based models (e.g., GPT) and associated applications
• Proficiency in programming languages such as Python and strong experience with machine learning frameworks and libraries
• Experience in developing and deploying embedding models
• Knowledge of intent recognition and prompt engineering techniques and best practices
• Detailed up to date understanding of RAI and ethics principles and challenges
• Excellent written, oral communication and advocacy skills, with demonstrable experience of prioritising effectively, managing diverse and multiple stakeholders
• Experience working, managing and leveraging resource and other benefits with third-party stakeholders
• Detailed understanding of SDLC & Engineering delivery methodology within a data and AI environment
  We know our people are the secret to our success. That’s why we’re always looking for ways to reward great work. You’ll find a host of benefits designed to work for you, including:

Company Pension

• Company Bonus
• Private Medical

AS PART OF THIS ROLE, YOU’LL BE RESPONSIBLE FOR:

• Lead AI Engineering resources to define and deliver Gen AI solutions on our Azure platform.
• Deliver solutions on other Gen AI platforms as prioritised by the AI Steering Committee and Transformation functions
• Build a formal LLM Ops process and capability and create associated standards in conjunction with our security and privacy teams
• Ensure delivery of robust and efficient Gen AI and ML operations and architectures.
• Develop and implement patterns to ingest and store unstructured data in relation to Gen AI Customer and colleague interactions for operational and analytical purposes
• Develop and fine-tune embedding models to convert text, images, and other data types into dense vector representations
• Design and build models for intent recognition to understand user inputs and improve interaction with AI systems
• Develop and implement semantic search capabilities using vector embeddings to provide more accurate search results
• Implement techniques for model optimization, including performance tuning and resource management on Azure
• Deploy AI models into production environments using containerization (Docker) and orchestration (Kubernetes)
• Manage the scaling of AI solutions to handle varying loads, ensuring high availability and reliability
• Work with Data and Portfolio project leads to deliver data and AI related projects
• Implement, maintain and evangelise best practices for AI and MLengineering
• Optimize performance, scalability, and efficiency of data pipelines and ML Ops processes
  This hands-on role will have accountability for the technical implementation and associated standards for Gen AI and ML solutions using approved toolsets in Currys. Specifically, it will be accountable for the successful adaptation and ongoing development of our Gen AI platform(s), ensuring compliance with business requirements and RAI principles.