AI/ML Solution Delivery: Hands on end-to-end development and deployment of both traditional and GenAI /Agentic AI based machine learning models, including discovery analytics, experimental design, model development, benchmarking, enhancement and deployment.
Model Design, Prompt Engineering & Evaluation: Design and execute experiments to benchmark and evaluate model performance using both classical metrics (precision, recall, F-score) and GenAI /Agentic AI specific techniques (LLM-as-a-Judge, ROUGE, GANs). Develop and refine prompts to optimize GenAI model reasoning, accuracy, and overall effectiveness.
Responsible AI: Apply strong understanding of ethical AI principles and governance frameworks, ensuring robust model validation and ongoing monitoring with regulatory and organizational standards.
Cross-Functional Collaboration: Work closely with business partners, stakeholders, and technical teams to translate business requirements into impactful AI solutions.
Research & Innovation: Stay abreast of emerging tools, techniques, and best practices in LLMs, RAG, GenAI, Agentic AI model development & evaluation techniques and proactively apply new knowledge to drive innovation.

PhD or MSc in Artificial Intelligence, Machine Learning, Computer Science or a related STEM field.
Strong foundation in core machine learning algorithms and deep learning concepts (e.g., Neural Nets, CNNs, GANs, RNNs, Transformers).
In-depth understanding of natural language processing (NLP) model development and large language model (LLM) fine-tuning, evaluation and ongoing monitoring framework.
Deep understanding of prompt engineering techniques, including zero-shot and few-shot prompting strategies with ability to enhance the performance of LLMs and agentic AI systems.
Solid grasp of data structures and handling for both structured (SQL, pandas) and unstructured (text, images, audio) data, including knowledge bases creation with Graph (Neo4j) and vector stores.
Proven track record in building, fine-tuning, and evaluating traditional ML, NLP and LLM-based models.
Hands-on experience with leading ML frameworks (e.g., PyTorch, TensorFlow) and LLM libraries (e.g., Hugging Face, LangChain/LangGraph, LlamaIndex).
Strong experience in stakeholder management, working closely with business owners, engineers, and governance teams to deliver AI initiatives end‑to‑end.
Experience in GenAI and AI Agent development and deployment using scalable cloud platforms (Azure, AI Foundry, Databricks, AWS).
Deep expertise in AI model evaluation framework and ongoing monitoring techniques.
Advanced programming skills in Python (and optionally, other languages such as R or Java).

Holiday: 182 hours (26 days)
Quilter Incentive Scheme: All employees are eligible to participate in incentive scheme, to incentivise business performance and their contribution.
Pension Scheme: A non-contributory company pension scheme that can be boosted through personal contributions.
Private Medical Insurance: Single cover as standard with options to increase cover to include your partner or children.
Life Assurance: 4x your salary.
Income Protection: 75% of salary, less state benefits, payable after 26 weeks of absence.
Healthcare Cash Plan: Jersey employees only.
In addition to our core benefits, we offer a range of flexible benefits to UK employees that you can choose from and pay for conveniently via a salary deduction.

Lead AI Scientist

Key skills