AI Research Engineer - AI Safety

At Helsing we deliver AI-based capabilities and the enabling foundation that allow machines to perceive and assist human decision-making. You will have the unique opportunity to shape AI capabilities in one of the most challenging sectors, where high generalisation capabilities need to be paired with robustness against adversarial attacks and the highest standards of operational safety. You will be responsible for defining operational domains and evaluating the reliability of AI capabilities developed in-house. Your work will span the full assurance lifecycle: from characterising distribution shifts and failure modes, to developing and extending the state of the art in uncertainty quantification and calibration. You will interface deeply with our AI systems, design rigorous evaluation frameworks, and assess their robustness under real-world and adversarial conditions, collaborating across research, engineering, and product teams to translate assurance findings into actionable improvements. You should apply if you hold an MSc in Mathematics, Statistics, Machine Learning, or a closely related field, with a strong mathematical and statistical foundation. Have hands-on experience in model evaluation, uncertainty quantification, or calibration. You understand the difference between epistemic and aleatoric uncertainty and know how to measure and reduce them in deep learning models. Are familiar with methods for distribution shift detection, out-of-distribution detection, and adversarial robustness evaluation, and can design experiments that surface genuine failure modes rather than benchmark artefacts.