The Core Amazon Machine Learning team in Cambridge develops innovative machine learning methods for the modeling and analysis of complex data. We collaborate closely with other science, engineering and product teams in Amazon in several application domains such as robotics, natural language understanding and many more. The particular research areas of the group are uncertainty quantification, data-efficient learning, streaming applications and privacy aware and deep learning. We focus on the mathematical and computational challenges that arise in these topics.
We are recruiting a curious and creative machine learning scientist intern who is prepared to learn new skills and who is willing to collaborate with scientists and engineers to implement new machine learning methods.
The internship will involve working on the deployment of innovative machine learning algorithms for the modelling and analysis of data. The candidate will be expected to work in research areas such as probabilistic modelling, surrogate model optimization, uncertainty quantification or probabilistic numerics. Specific challenges will be dealing with very large datasets and designing algorithms able return uncertainties in their calculations.