krakentech - Head of R&D

• We're looking for an exceptional technical leader who has demonstrated the ability to develop advanced AI technology and turn it into real-world impact. • We're more interested in what you've built, the problems you've solved and the technical depth you bring than a particular job title. • Deep expertise in modern machine learning and deep learning, with a strong understanding of foundation models, model architectures, and data pipelines. • A proven track record of designing, developing or leading the creation of advanced AI models that have delivered measurable technical or commercial outcomes. • Strong technical knowledge of several areas such as transformer architectures, foundation-model training and adaptation, representation learning, time-series modelling, reinforcement learning and related machine learning techniques. • Experience working with large, complex datasets and developing models capable of identifying meaningful patterns, generalising across problems and operating at scale. • A strong understanding of the end-to-end model development lifecycle, including data preparation, training, evaluation, experimentation, inference and production deployment. • Experience building, leading or technically guiding high-performing teams of machine learning engineers, research engineers or applied AI specialists. • The ability to translate ambitious technical ideas into clear strategies, practical roadmaps and systems that create meaningful business value. • Strong technical judgement, including the ability to evaluate emerging approaches, challenge assumptions and make pragmatic decisions about where to invest. • The ability to communicate complex technical concepts clearly and influence senior engineering, product and executive stakeholders. • TECHNICAL EXPERTISE • You'll bring significant depth in some of the following areas: • Foundation models, large language models and transformer-based architectures. • Large-scale pre-training, fine-tuning, distillation and model evaluation. • Time-series foundation models, representation learning and alternative approaches to structuring and tokenising complex data. • Reinforcement learning, decision-making models and learning-based optimisation. • Distributed model training and modern deep learning frameworks such as PyTorch or JAX. • Scalable data pipelines, training infrastructure, inference systems and production ML engineering. • Model evaluation, experimentation and techniques for improving performance, reliability and generalisation. • We don't expect you to be an expert in every area. What matters most is deep technical expertise, the ability to recognise promising approaches and the judgement to build the right capabilities around you. • PhD Machine Learning, neuroscience, Computer Science, Physics or a related discipline. • Experience developing foundation models or advanced AI systems using large-scale data. • Nice to have: experience with energy systems, electricity markets, demand forecasting, grid flexibility or other complex physical systems. • Experience applying AI to scientific, industrial or real-world decision-making problems. • Experience developing novel model architectures or achieving state-of-the-art results in a commercially relevant domain. • Experience establishing a new technical team, capability or product area from an early stage. • Are you ready for a career with us? We want to ensure you have the right tools and environment to unleash your potential. If you have any accommodation requests, please contact us at [email protected]. We’ll do our best to tailor the experience to your needs so you can feel comfortable, confident and be at your best!