Principal Deep Learning Engineer

  • AstraZeneca
  • Cambridge CB23, UK
  • 11/02/2020
Full time Data Science Data Engineering Data Analytics Statistics

Job Description

Role

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.

Key Accountabilities

  • Investigate innovative machine learning, artificial intelligence and statistic techniques for health data challenges.
  • Collaborate with scientists and other machine learning engineers and data scientists to translate medical problems into machine learning problems.
  • Design and implement machine learning pipelines.
  • Design, implement and evaluate machine learning models solve problems faced by our drug development scientists, e.g., disease progression analysis in CT scans.
  • Deploying machine learning solutions into production.
  • Optimizing solutions for performance and scalability.
  • Explain analyses and machine learning solutions to technical audiences.
  • Liaise with other teams to enhance our technological stack, to enable the adoption of the latest advances in Data Processing and AI.
  • Support the strategic planning of the team by providing leadership as well as mentor and support the team of engineers across multiple projects.

Candidate Knowledge, Skills and Experience

Essential

  • A PhD, in Computer Science, Applied Mathematics, Artificial Intelligence, Statistics or related subjects – or Masters in a relevant discipline and exceptional Machine Learning skills.
  • 2+ years of experience and demonstrable deep technical skills in one or more of the following areas: machine learning, recommendation systems, pattern recognition, natural language processing or computer vision.
  • 1+ year of experience with one or more DL frameworks such as Tensorflow or PyTorch.
  • Experience with scientific and machine learning libraries e.g., SciPy, Scikit-learn, NumPy.
  • Strong software development skills. Proficiency in Python preferred.
  • Experience building large scale data processing pipelines.
  • Experience with Cloud computing, Hadoop/Spark, SQL.
  • Ability to explain and present analyses and machine learning concepts to a broad audience.
  • Ability to work with loosely defined objectives and turning these into concrete machine learning problems.
  • Creative, collaborative, & product focused.

Desirable

  • Experience training and deploying machine learning models at scale on distributed cloud environments
  • Experience applying machine learning in the healthcare domain.
  • Experience with reinforcement learning is a plus

Other

The role will have no direct line reports, but task management responsibilities within project or services may occur