MLOps Platform Engineer

The Enterprise AIProductsandTechnologyTeamare responsible forbuilding and running the platforms,toolingand infrastructure that powers AstraZeneca’s ambition to use AI in every step of the value chain, from discovering new compounds to patient safety systems. 

We are looking for a MLOps engineer to join our Enterprise AIProducts and TechnologyTeam. The ideal candidate will have industry-relevant experience delivering at scale Machine Learning or Data Scienceprojects.

You will be part of a collaborative team ofmultidisciplinary engineers andworking 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 tobettersuit the datascientistways of working.Our data science teamsundertakemajor AI initiatives such as clinical trial data analysis, knowledge graph analytics, patient safety systems, deep learning led drug discovery, softwareas a medical device system.

Asa MLOps engineer, you have the software engineering mindset towards automation and agility while being able to question and improve the ways ofworking ofdata 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 thetools/platformsthatunderpinstheir research.

• Be a part of a high performing agile team, continuously improving AstraZeneca’s Machine Learning development environments,platformsand toolingto 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 seamlesslyscale exploratory research to production. 

Candidate Knowledge,Skillsand Experience

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

• Demonstrableexperience in software engineering and automationleveragingDevOps.

• Prior experience withdeveloping and deploying production grade machine learning products or exceptional ability in other software engineering domainswillbe considered.

• 3 years ormore ofexperience 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,collaborativeand resilient. 

WHYJOINIT?

We’rea network of entrepreneurialself-starterswho contribute to somethingfar bigger.There’sa diversity ofexpertisein ourTechnology groupthat’sunique toAstraZeneca – it allows us to dive deep intoexploring new leading-edge technology.We enable AstraZeneca to perform at itspeak by delivering world-class technologyand data solutions.Our work unlocks the potential of science.We optimise andevolutioniseAstraZenecabymaximising efficiencies and finding newways to drive productivity. From automationto data simplification.We’renot afraid to take ownership and runwith it. Empowered withunrivalled freedom.A place to be open andtransparent – we speakup, thinkcreativelyand share ideas. Our diversecontributions help us to make better decisions.But we have a constant drive to innovate,and an appreciation forhigh standards.It takes challenging the status quo to addvalue in our ever-evolving environment.We love itherebecauseput simply, we make a meaningful impact.