Senior Machine Learning Ops Engineer - Biologics Discovery Platform
ABOUT ASTRAZENECA
AstraZeneca is a global, innovation-driven BioPharmaceutical business that focuses on the discovery, development and commercialisation of prescription medicines for some of the world’s most serious disease. But we’re more than one of the world’s leading pharmaceutical companies.
At AstraZeneca, we're dedicated to being a Great Place to Work. Where you are empowered to push the boundaries of science and spark your entrepreneurial spirit. There’s no better place to make a difference to medicine, patients and society. An inclusive culture that champions diversity and collaboration. Always committed to lifelong learning, growth and development.
About the project
At AstraZeneca, we're not just about creating life-changing medicines; we're about creating a culture of innovation and collaboration. We have taken on an ambitious goal of revolutionizing antibody discovery at AstraZeneca by significantly reducing the time it takes to discover a clinical candidate using world-class technology and sophisticated data & AI capabilities. To support this initiative, we are building Biologics Discovery Platform within the R&D IT.
About the role
In this role you will join a global team of engineers (software, data, MLOps), architects, BAs, PMs, in our Biologics Discovery Platform to support biologics and antibody drug discovery as a Senior MLOps Engineer. The following will form part of the role:
Responsible for productionsing generative and predictive models and support the full model life cylce (code optimisation, deployment, retraining, publishing, monitoring, etc.)
Responsible for designing, implementing, and integrating AI/ML solutions to make our science faster and more efficient to do, easier to learn from, and offer faster delivery and higher quality across biologics discovery.
Collaborate with product, design, data science, and our scientific teams to build innovative AI/ML products and services
Advocate and advance modern, agile MLOps practices and help develop and evangelize a vibrant AI/ML software engineering culture
Plan, implement and support core infrastructure development collaboratively with an overall objective to improve the scalability, reliability, performance, and availability of ML services
Advocate for rigorous engineering practices and discipline: code reviews, automated testing, logging, monitoring, alerting, etc.
Passionate to stay on top of tech trends in AI/ML, experiment with and learn new technologies, participate in internal & external technology communities, and mentor other members of the engineering community
Working with cutting edge technology stack in cloud environment
About you
Expertise in Python and ML libraries
Experience designing, implementing generative and predictive AI applications
Solid experience using/building MLOPs platforms at scale covering full model life cycle management (ML pipelines, docker, Kubernetes, REST API based ML inference, model registry, etc.)
Experience using relational databases (PostgreSQL, Oracle) and NoSQL databases (Elastic Search/ MongoDB).
Experience of data analysis – profiling, investigating, interpreting, and documenting data structures.
Experience in performance tuning SQL and understanding ETL pipelines.
Extensive experience in solving data issues, analyzing end to end data pipelines, and web service performance
Good experience in consuming or exposing web APIs
Design, develop, and deploy production-grade scalable AI/ML APIs using container technologies like Docker and Kubernetes.
Production experience delivering CI/CD pipelines (Jenkins, ArgoCD, TravisCI, Git).
Experience in creating and critically evaluating MLOps architecture in the cloud
Excellent verbal and written skills for effective communication with a variety of personas including, engineers, testers, architects, product managers, scientists, etc.
The following skills would be advantageous for your application but are not considered crucial:
Experience working with AWS - advantage.
Bioinformatics / Computational or molecular biology background.
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.