• Strong foundation in machine learning, with hands-on experience in model development and experimentation.

• Strong programming proficiency in Python and extensive experience with ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn).

• Ability to analyze model behavior, diagnose training issues, and design experiments to optimise performance and reliability

• Demonstrated ability to read, synthesise, and critically evaluate academic research papers and technical literature

• Experience designing and conducting rigorous experiments to validate hypotheses and measure solution effectiveness

• Comfort working with ambiguous problems and developing novel approaches to complex challenges

• Experience with privacy-enhancing technologies, including but not limited to anonymisation, synthetic data generation or differential privacy.

• Familiarity with frontend integration workflows (Next.js/React).

• Prior experience working in multi-disciplinary teams.