Research Engineer

An exciting opportunity has arisen for an experienced Research Engineer to join a world-class team working at the forefront of AI research and engineering.The successful candidate will work alongside leading researchers and engineers, developing novel approaches to challenging AI problems and translating cutting-edge research into impactful real-world applications.This is an excellent opportunity for someone who wants to work at the intersection of research and engineering, with the opportunity to contribute to publications at leading AI conferences and collaborate with prominent academic and industry partners.The RoleDevelop and implement novel machine learning algorithms and techniquesWork closely with world-class researchers and engineers on challenging AI problemsExplore new approaches across areas including reinforcement learning, large language models and optimisationTranslate research concepts into practical, scalable implementationsContribute to research suitable for publication at leading AI conferencesCollaborate with leading academic and industry partnersExperience RequiredThe ideal candidate will have:Deep expertise in at least one of the following areas:Reinforcement Learning (RL)Large Language Models (LLMs)Optimisation for Deep Learning Strong experience implementing machine learning algorithms and techniquesA strong interest in AI research and emerging technologiesThe ability to work collaboratively within a highly talented research and engineering environmentWhy Consider This Opportunity?Work on cutting-edge AI challenges with a talented, multidisciplinary teamCollaborate with leading academic and industry partnersAccess high-performance computing resourcesWork on novel AI research with the potential for significant real-world impactPublish research at leading conferences including NeurIPS, ICML and ICLRWork alongside some of the leading researchers and engineers in the fieldLocationThe position can be based in either Cambridge or London, near King’s Cross.The organisation currently operates a hybrid working model, with 4 days per week in the office and 1 day working from home.