ASSOCIATE PRINCIPAL AI ENGINEER

Introduction to role.
his role is based in  Barcelona, with an on-site commitment of three days a week.
Fluency in  English  is required Are you ready to make a difference? At AstraZeneca, we connect across the entire business to enhance patient outcomes and improve lives.
As an Associate Principal AI Engineer, you'll play a pivotal role in driving transformative change on our journey to becoming a digital and data-led enterprise.
Harness the power of cutting-edge innovations in data, machine learning, and technology to transform complex information into actionable insights.
Collaborate with leading experts in our specialist communities, where diverse minds come together to create novel solutions.
This is your chance to shape the future of an evolving business in the technology space! Accountabilities.
Join the Enterprise AI Products and Technology Team, responsible for building and running platforms, tooling, and infrastructure that enable AstraZeneca's AI ambitions across the value chain.
As an ML Ops engineer, you'll work closely with multidisciplinary teams to create tools, standards, and automate tasks within the machine learning product lifecycle.
Enhance platform capabilities to align with data scientists' ways of working and contribute to major AI initiatives such as clinical trial data analysis and deep learning-led drug discovery.
Embrace a software engineering mindset towards automation and agility while continuously improving data science processes.
Essential Skills/Experience.
Bsc/MSc/Ph.
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.
Desirable Skills/Experience.
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.
At AstraZeneca, technology is a key lever in delivering medicines quickly, affordably, and sustainably.
Be part of a dynamic environment where change is embraced, new solutions are trialed, and data is leveraged to improve processes for those in need.
Our diverse workforce is united by curiosity, sharing learnings and scaling fast.
Experience the support and investment from our leaders as we accelerate our digital journey forward.
Ready to make an impact? Apply now and join us on this exciting journey! Date Posted 26-jun- Closing Date 16-jul- AstraZeneca embraces diversity and equality of opportunity.
We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills.
We believe that the more inclusive we are, the better our work will be.
We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics.
We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.
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