The Enterprise AI Products and Technology Team are responsible for building and running the platforms, tooling and infrastructure that powers AstraZeneca’s ambition to use AI in every step of the value chain, from discovering new compounds to patient safety systems.   

You will be part of a collaborative team of multidisciplinary engineers and working closely with data science teams, have a chance to create tools, standards and automate commonly used tasks of machine learning product lifecycle. A part of the role is also to increase the capabilities of the platforms team to better suit the data scientist ways of working. Our data science  teams  undertake major AI initiatives such as clinical trial data analysis, knowledge graph analytics, patient safety systems, deep learning led drug discovery, software as a medical device system. 

 As an  Associate Principal AI Engineer you have the software engineering mindset towards automation and agility while being able to question and improve the ways of working of data science teams.  

Key Accountabilities  

• Collaborate with Data Scientists and Machine Learning Engineers  from across the company to understand their challenges and work with them to  build  the  tools/platforms  that  underpins  their  research.   

• Be a part of a high performing agile team, continuously improving  AstraZeneca’s Machine Learning development environments,  platforms and tooling to better suite data science initiatives. 

• Work closely and collaboratively with internal governance and compliance functions such as Cyber Security and Data Privacy to secure our estate without obstructing end-user productivity.   

• Adapt standard machine learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU).  

• Champion a “production first mindset” in the data science projects development lifecycle to seamlessly scale exploratory research to production.   

 Candidate Knowledge, Skills and Experience   

• Bsc/MSc/Ph.D degree in Computer Science or related quantitative  or analytical field.  

• Demonstrable experience in software engineering and automation  leveraging DevOps.  

• Prior experience with developing and deploying production grade machine learning products or exceptional ability in other software engineering domains will be considered. 

• 3 years or more of experience building and delivering software using the Python programming language, exceptional ability in other programming languages will be considered. 

• In depth knowledge and experience with at least one container orchestration framework (Airflow, Argo, Kubeflow etc) or willingness to learn. 

• Demonstratable experience deploying the underlying infrastructure and tooling for running Machine Learning or Data Science at Scale  using Infrastructure of Code.

• Experience working in an Agile team.  

• Experience working with internal security standards and  frameworks.

• Creative, collaborative and resilient.  

When we put unexpected teams in the same room, we unleash bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. That's why we work, on average, a minimum of three days per week from the office. But that doesn't mean we're not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.