We are looking for a Deep Learning Engineer to join our AI Engineering team in Cambridge or Gothenburg. The ideal candidate will have industry experience developing and applying Machine Learning and Deep Learning solutions, e.g. developing data pre-processing pipelines, modelling, training state of the art deep neural networks (CNNs/RNNs/LSTMs/Transformers) as well as deploying inferencing pipelines to process unseen data at scale. The position will involve taking these skills and applying them to some of the most exciting data & prediction problems in drug discovery. You will work as part of a global team of deeply technical data scientists, knowledge engineers & machine learning engineers and have the chance to create tools that will advance the standard of healthcare improving the lives of millions of patients across the globe.
We are working in collaboration with our scientists to help develop better drugs faster, choose the right treatment for a patient and run safer clinical trials. Our team empowers our scientists from early development to the late stages in drug development, driving innovation and acting as a catalyst for the adoption of the latest advances in Artificial Intelligence and Data Science. You will work closely with scientists & product teams and learn to deliver DL solutions at scale within the AstraZeneca tech stack, whilst encouraging best practices for DL across the company.
We are looking for deep learning engineers capable of building robust, accurate DL-based systems and scientifically rigorous solutions that will be used across scientific units in AstraZeneca. As a strong software leader and an expert in building complex systems, you will be responsible for inventing how we use technology, Deep Learning and data to enable the productivity of AstraZeneca.
You will help envision, build, deploy and develop our next generation of analytical engines at scale.
Candidate Knowledge, Skills and Experience
The role will have no direct line reports, but task management responsibilities within project or services may occur