AI Platform Engineer

The Enterprise AI Platforms and Operations Team is responsible for building and running the platforms, tooling, and infrastructure that powers AstraZenecas ambition to use AI in every step of the value chain, from discovering new compounds to patient safety systems. We achieve this through a combination of technical leadership and agile-focused development, continuously evaluating the fast-moving advancements in Machine Learning tooling for challenges across AstraZenecas R D, Commercial, and Operations domains. We deliver these tools through easy-to-access environments that allow AstraZenecas Data Scientists and Machine Learning Engineers to focus on building groundbreaking solutions for patients at scale., We are looking for an AI Platform Engineer to join our Enterprise AI Platforms and Operations Team. The ideal candidate will have industry-relevant experience delivering at scale Machine Learning or Data Science in the AWS cloud ecosystem or its competitors. You will be part of a collaborative team of multidisciplinary engineers and together have the chance to create tools that will advance the standard of healthcare, improving the lives of millions of patients across the globe. Our data science platforms will support major AI initiatives such as clinical trial data analysis, knowledge graph analytics, patient safety systems, deep learning-led drug discovery, and software as a medical device systems.

As an AI Platform Engineer with an interest in building complex systems, you will be responsible for inventing how we use technology, machine learning, and data to enable the productivity of AstraZeneca. You will help build, deploy, and develop our next generation of platforms and tools at scale.

Accountabilities

• Collaborate with Data Scientists and Machine Learning Engineers across the company to understand their challenges and build the platform that underpins their research.
• Be part of a dedicated agile team, continuously improving AstraZenecas Machine Learning development environments, platforms, and tooling.
• Work closely 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 attitude to ensure the necessary infrastructure and platforms are available to scale exploratory research to production.

Bsc/MSc/Ph.D degree in Computer Science or related quantitative or analytical field. Experience as a founder, entrepreneur or experienced consultant will be looked at equally.

• Demonstratable experience working with AWS or a similar cloud environment
• Experience working with Kubernetes and/or container-based application deployments.
• Administering a production cluster, with an understanding of operators, storage classes and service meshes.
• Experience building and delivering software using the Python programming language, exceptional ability in other programming languages will be considered.
• Demonstratable experience deploying the underlying infrastructure and tooling for running Machine Learning or Data Science at Scale using Infrastructure of Code
• Experience using DevOps to enable automation strategies
• Experience or awareness of MLOps practices and building pipelines to accelerate and automate machine learning will be looked upon favorably
• Experience working in an Agile team with knowledge or experience of working in product or platform-focused delivery.
• Experience working with internal security standards and frameworks. Especially within a medical, clinical or pharmaceutical context.
• Experience working with GxP compliant life science systems will be looked upon favorably
• 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. Thats why we work, on average, a minimum of three days per week from the office. But that doesnt mean were not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.