Generative AI Research Scientist

Join us as a Generative AI Research Scientist. You’ll drive innovation in how the bank applies generative AI (GenAI), identifying high-value opportunities, proving what works, and shaping next-generation products and customer experiences.

Act as the bank's technical authority on GenAI, guiding internal adoption while representing our capabilities externally across the wider AI community. You’ll have the opportunity to work at the cutting edge of generative AI, exploring emerging techniques and turning research into real-world solutions that deliver impact at scale.

What you’ll do:

• Bring strong research rigour to everything you do, from problem framing and model selection to building defensible, evidence-based outcomes.
• Explore and evaluate emerging techniques, including new model families, retrieval-augmented generation, agentic patterns and multimodal approaches, and run experiments to determine what works best for the business.
• Lead the strategy for customisation, deciding on what to fine-tune, which data to use, and how success is measured.
• Translate complex business challenges into clear machine learning problems and identify which GenAI approaches are worth pursuing and why.
• Stay at the forefront of scientific advancements, applying the latest research to uncover new opportunities and drive innovation across the bank.
• Take ownership of evaluation, designing robust benchmarks, test sets and statistical analyses to assess accuracy, safety, bias and model robustness.
• Prototype innovative GenAI solutions, working with product and business teams to test ideas and validate them using real users and data.
• Define quality and safety standards, setting the bar solutions must meet before scaling across the organisation.
• Advise on model risk, interpretability, and regulatory considerations so proposed approaches are robust, transparent, and fit for purpose.
• Publish research and contribute to intellectual property, including papers, patents or recognised contributions to the applied GenAI community.
• Collaborate with interdisciplinary teams, including research and software engineers and cross-functional partners, to develop solutions that support the productionisation of research outcomes.

The skills you'll need:

• A strong foundation in machine learning, statistics and experimental design, combined with hands-on experience in fine-tuning, prompt engineering and rigorous model evaluation.
• A deep understanding of GenAI architectures and their trade-offs, along with the ability to design experiments, interpret results and defend conclusions using robust, evidence-based approaches.
• Strong judgement in identifying high-impact opportunities, paired with the ability to assess which problems are tractable and which approaches will deliver meaningful outcomes.
• An understanding of model risk, data governance and financial-services regulation.
• The ability to communicate complex ideas clearly, engaging both technical and non-technical stakeholders, including risk and compliance teams.
• Sound decision-making in selecting appropriate methods and techniques, applying the right tools to solve problems effectively and efficiently.
• A track record of taking GenAI concepts from idea to validated proposition, demonstrating the ability to translate research into practical, real-world impact.