Responsible AI/ML Scientist (KTP Associate)

Duel, in partnership with the University of Bristol, has an opportunity for a highly skilled & qualified graduate to lead and deliver a Knowledge Transfer Partnership (KTP) project to develop a new process for bias detection and AI explainability that will enhance the efficiency and effectiveness of Duel’s brand advocacy platform. You will be able to apply your degree in real world applications with the role, providing an introduction to industrial and commercial work whilst retaining links to academia.

You will:

• Review Duel’s AI/ML workflows to identify opportunities for improved fairness, explainability, and decision lineage.
• Design and develop methods for bias detection, bias mitigation, explainable AI and trustworthy decision-making.
• Build software prototypes that can be embedded into Duel’s platform and product workflows.
• Evaluate the proposed methods using appropriate technical, ethical and user-centred criteria.
• Work closely with Duel’s product, engineering and leadership teams, supported by academic supervisors at the University of Bristol.
• Produce documentation, guidance and processes to help Duel adopt responsible-AI practices beyond the project.
• Disseminate findings through conferences, meetings, workshops and, where appropriate, academic publications.
• Lead the project day to day, including managing your workload, running meetings and workshops, solving problems, and shaping the project plan.

You should apply if you have:

• A First degree or equivalent in Computer Science, Artificial Intelligence, Data Science, or a related discipline (a PhD, or near-completed PhD, is desirable; exceptional Master’s-level candidates with strong relevant experience will also be considered)
• Strong knowledge of AI and machine learning, with software engineering experience.
• Experience or understanding of fairness, bias mitigation, explainable AI, decision lineage, ethical AI, AI auditing or trustworthy AI.
• A research profile or applied experience relevant to venues such as AIES, FAccT, AAAI, or IJCAI.
• Excellent communication and problem-solving skills, with the ability to work across academic, technical and business teams.
• Confidence to lead an applied research project, adapt to changing needs, and translate research into practical impact.

The project will develop new methods, tools and processes to help Duel identify, explain and manage bias in AI-assisted decisions across its brand advocacy platform. It will support the development of more transparent, auditable and trustworthy AI capabilities, enhancing both the effectiveness of the platform and confidence in its use.