Senior AI/ML Scientist

Quilter • London, VA

3d • Hybrid

About The Position

The new role sits within the AI Centre of Excellence department under the Chief Operating Office (COO). This position involves hands-on, end-to-end development and deployment of both traditional and GenAI-based machine learning models. Key responsibilities include discovery analytics, experimental design, model development, benchmarking, enhancement, and deployment. The role also requires designing and implementing new Retrieval-Augmented Generation (RAG) pipelines and enhancing existing frameworks using advanced techniques. Evaluating model performance using classical and GenAI-specific metrics, and optimizing GenAI model reasoning through prompt engineering are crucial. Collaboration with business partners, stakeholders, and technical teams to translate business requirements into impactful AI solutions is expected. The role also involves staying abreast of emerging tools and techniques in LLMs, RAG, and GenAI, and proactively applying new knowledge to drive innovation.

Requirements

• Advanced degree (MSc or PhD) in Machine Learning, Natural Language Processing, Artificial Intelligence, or a related field.
• Proven track record of delivering AI solutions from research to production in real-world applications.
• Strong foundation in machine learning algorithms and deep learning concepts including Neural Networks and Transformer-based architectures.
• Knowledge in developing and deploying scalable models on Databricks, Azure, and AWS, leveraging tools such as FastAPI and Docker.
• Proficient in model tracing and observability for LLM in production and implementing evaluation frameworks for model quality and reliability.
• Strong understanding of software engineering best practices, including version control, testing, and CI/CD for production-ready AI systems.
• Strong experience in AI/ML research and development, specializing in deep learning-based NLP, Information Retrieval, and Generative AI.
• Proven expertise in RAG/GraphRAG pipeline development and evaluation, including advanced retriever-reranker techniques.
• Extensive experience in defining and implementing evaluation metrics for GenAI systems such as Recall, Precision, NDCG, LLM-as-a-Judge, BERTScore, BLEU score, and hallucination detection.
• Strong proficiency in Python and experience with frameworks such as NumPy, Pandas, Scikit-learn, and modern Generative AI libraries (e.g., LangChain, LlamaIndex, Azure AI Foundry).
• Hands-on experience with PyTorch, and leading LLM libraries such as Hugging Face, LangChain, LangGraph, and LlamaIndex.
• Skilled in hypothesis formulation, defining evaluation metrics, conducting literature reviews, and building reproducible prototypes with critical outcome analysis.
• Comfortable with a fail-fast, learn-fast approach, iterating quickly to validate ideas and accelerate innovation.
• Exceptional problem-solving skills and a strong passion for innovation.
• Excellent communication and collaboration abilities, thriving in cross-functional environments.

Nice To Haves

• Domain expertise in financial services or other regulated industries is highly desirable.
• Experience in building knowledge bases and ontologies is highly desirable.

Responsibilities

• Hands-on end-to-end development and deployment of both traditional and GenAI-based machine learning models, including discovery analytics, experimental design, model development, benchmarking, enhancement and deployment.
• Design and implement new Retrieval-Augmented Generation (RAG) pipelines and enhance existing frameworks, applying advanced techniques in data chunking/splitting, vectorization, knowledge graph representation (GraphRAG), and query retrieval and evaluation.
• Design and execute experiments to benchmark and evaluate model performance using both classical metrics (precision, recall, F-score) and GenAI-specific techniques (LLM-as-a-Judge, ROUGE, BERTScore).
• Develop and refine prompts to optimise GenAI model reasoning, accuracy, and overall effectiveness.
• Work closely with business partners, stakeholders, and technical teams (data engineering, platform engineering) to translate business requirements into impactful AI solutions.
• Stay abreast of emerging tools, techniques, and best practices in LLMs, RAG, GenAI, model development & evaluation techniques and proactively apply new knowledge to drive innovation.
• Provide mentorship and technical guidance to junior AI Scientists.

Benefits

• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior