Job Title: Senior Manager - AI Platform Career Level - E Introduction to Role:Join the Enterprise AI Platforms and Technologies Team at AstraZeneca, where we are building and running the platforms, tooling, and infrastructure that powers our ambition to use AI in every step of the value chain. We are looking for an AI Platform/MLOps Engineer to join our team. You will be part of a collaborative team of multidisciplinary engineers and have the chance to create tools that will advance the standard of healthcare, improving the lives of millions of patients across the globe.
Accountabilities:As an AI Platform/MLOps Engineer, you will collaborate with Data Scientists and Machine Learning Engineers from across the company to understand their challenges and work with them to build the platform that underpins their research. You will be part of a hard-working agile team, continuously improving AstraZeneca's enterprise Machine Learning development environments, platforms, and tooling. You will also work closely and collaboratively with internal cross-functional teams to secure our estate without obstructing end-user productivity.
Leadership and Collaboration Ability to drive conversations and collaborate with product managers, data scientists, and other stakeholders to align technical solutions with business objectives.
Strong leadership and interpersonal skills to lead cross-functional technical teams effectively.
Ability to coach junior technical members.
Technical Leadership and Expertise Strong analytical and problem-solving skills to address challenges.
Solid and creative technical leadership skills to drive detailed design and fact-based decision-making.
Strong ability to create and communicate designs to engineers that are scalable and efficient AI platforms; implement and maintain the infrastructure and platforms that support the development and deployment of AI solutions.
Experience in DevOps/MLOps/AIOps practices to streamline the development and deployment processes.
Strong programming skills in Infrastructure as Code (e.g., Terraform, CloudFormation), AWS Services, collaborative software development, programming languages used in AI such as Python, proficiency in containerization technologies like Docker, etc.; and the ability to write clean, efficient, and maintainable code.
Familiarity with big data technologies, including Apache Spark and Hadoop, for processing and analyzing large datasets.
Understanding of security best practices in AI systems and adherence to compliance standards.
Willingness to stay updated with the latest advancements in AI technologies through continuous learning and professional development.
Actively contributes to the continuous improvements/roadmaps of existing AI platforms.
Essential Skills/Experience:- BSc/MSc/PhD in Computer Science or related quantitative or analytical field.- Demonstratable experience working with AWS.- Experience working with Kubernetes and/or container-based application deployments.- Experience administering a production cluster, with an understanding of operators, storage classes, and service meshes.- Experience building and delivering software using Python and 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 as Code.- Experience using DevOps to enable automation strategies.- Experience in MLOps practices and building pipelines to accelerate and automate machine learning.- Experience working in an Agile team with knowledge or experience in product or platform-focused delivery.- Experience in data science/ML journey, from model experimentation to industrialization.- Experience working with internal security standards and frameworks, especially in medical, clinical, or pharmaceutical contexts.- Experience working with GxP-compliant life science systems.- Creative, collaborative, and resilient.
Desirable Skills/Experience:- AWS Certified DevOps Engineer- AWS Certified Developer
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.
Why AstraZeneca?At AstraZeneca, we dare to lead, applying our problem-solving mindset to identify and tackle opportunities across the whole enterprise. Our spirit of experimentation is lived every day through our events like hackathons. We enable AstraZeneca to perform at its peak by delivering world-class technology and data solutions. Our work unlocks the potential of science. We optimise and revolutionise AstraZeneca by maximising efficiencies and finding new ways to drive productivity. From automation to data simplification.
Join us at a crucial stage of our journey in becoming a digital and data-led enterprise. Make the impossible possible by building partnerships and ecosystems, creating new ways of working and driving scale and speed to deliver exponential growth. Focused and committed, and backed with the investment to succeed, we're driving cross-company change to disrupt the entire industry.
Ready to make a difference? Apply now!
Date Posted
28-Feb-2024 Closing Date
13-Mar-2024 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.
