Senior MLOps Platform Engineer
Role details
Job location
Tech stack
Job description
The Enterprise AIProductsandTechnologyTeam 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., * Collaborate with Data Scientists and Machine Learning Engineers from across the company to understand their challenges and work with them to build thetools/platformsthat underpins their research.
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Be a part of a high performing agile team, continuously improving AstraZeneca's Machine Learning development environments, platforms and toolingto better suite data science initiatives.
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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.
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Adapt standard machine learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU).
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Champion a "production first mindset" in the data science projects development lifecycle to seamlesslyscale exploratory research to production.
Requirements
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 data scientist ways 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, software as a medical device system.
As a ML Ops 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., * Bsc/MSc/Ph.D degree in Computer Science or related quantitative or analytical field.
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Demonstrableexperience in software engineering and automationleveraging DevOps.
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Prior experience withdeveloping and deploying production grade machine learning products or exceptional ability in other software engineering domainswillbe considered.
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3 years or more of experience building and delivering software using the Python programming language, exceptional ability in other programming languages will be considered.
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In depth knowledge and experience with at least one container orchestration framework (Airflow, Argo, Kubeflow etc)or willingness to learn.
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Demonstratable experience deploying the underlying infrastructure and tooling for running Machine Learning or Data Science at Scale using Infrastructure of Code
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Experience working in an Agile team
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Experience working with internal security standards and frameworks
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Creative, collaborative and resilient.