Machine Learning/ai Operations Engineer

Introduction to role Are you ready to be part of the future of healthcare Can you think big be bold and harness the power of digital and AI to tackle longstanding life sciences challenges Then Evinova a new healthtech business within the AstraZeneca Group might be for you Transform billions of patients lives through technology data and cutting-edge ways of working You re disruptive decisive and transformative someone who s excited to use technology to improve patients health We re building Evinova a fully-owned subsidiary of AstraZeneca Group to deliver market-leading digital health solutions that are science-based evidence-led and human experience-driven Smart risks and quick decisions come together to accelerate innovation across the life sciences sector Be part of a diverse team that pushes the boundaries of science by digitally empowering a deeper understanding of the patients we re helping Launch game-changing digital solutions that improve the patient experience and deliver better health outcomes Together we have the opportunity to combine deep scientific expertise with digital and artificial intelligence to serve the wider healthcare community and create new standards across the sector Accountabilities The Machine Learning and Artificial Intelligence Operations team ML AI Ops is newly formed to spearhead the design creation and operational excellence of our entire ML AI data and computational AWS ecosystem to catalyze and accelerate science-led innovations This team is responsible for the design implementation deployment health and performance of all algorithms models ML AI operations MLOps AIOps and LLMOps and Data Science Platform We manage ML AI and broader cloud resources automating operations through infrastructure-as-code and CI CD pipelines ensuring best-in-class operations striving to push beyond mere compliance with industry standards such as Good Clinical Practices GCP and Good Machine Learning Practice GMLP As a ML AI Operations Engineer for clinical trial design planning and operational optimization on our team you will lead the development and management of MLOps systems for our trial management and optimization SaaS product You will collaborate closely with data scientists to transition projects from embryonic research into production-grade AI capabilities utilizing advanced tools and frameworks to optimize model deployment governance and infrastructure performance This position requires a deep understanding of cloud-native ML AI Ops methodologies and technologies AWS infrastructure and the unique demands of regulated industries making it a cornerstone of our success in delivering impactful solutions to the pharmaceutical industry Role Team Key Responsibilities Operational Excellence Lead by example in creating high-performance mission-focused and interdisciplinary teams culture founded on trust mutual respect growth mindsets and an obsession for building extraordinary products with extraordinary people Drive the creation of proactive capability and process enhancements that ensures enduring value creation and analytic compounding interest Design and implement resilient cloud ML AI operational capabilities to maximize our system A-bilities Learnability Flexibility Extendibility Interoperability Scalability Drive precision and systemic cost efficiency optimized system performance and risk mitigation with a data-driven strategy comprehensive analytics and predictive capabilities at the tree-and-forest level of our ML AI systems workloads and processes ML AI Cloud Operations and Engineering Develop and manage MLOps AIOps LLMOps systems for clinical trial design planning and operational optimization Partner closely with data scientists to shepherd projects from embryonic research stages into production-grade ML AI capabilities Leverage and teach modern tools libraries frameworks and best practices to design validate deploy and monitor data pipelines and models in production examples include but are not limited to AWS Sagemaker MLflow CML Airflow DVC Weights and Biases FastAPI Litserve Deepchecks Evidently Fiddler Manifold Establish systems and protocols for entire model development lifecycle across a diverse set of algorithms conventional statistical models ML and AI GenAI models to ensure best-in-class Machine Learning Practice MLP Enhance system scalability reliability and performance through effective infrastructure and process management Ensure that any prediction we make is backed by deep exploratory data analysis and evidence interpretable explainable safe and actionable Personal Attributes Customer-obsessed and passionate about building products that solve real-world problems Highly organized and detail-oriented with the ability to manage multiple initiatives and deadlines Collaborative and inclusive fostering a positive team culture where creativity and innovation thrive Essential Skills Experience - Deep understanding of the Data Science Lifecycle DSLC and the ability to shepherd data science projects from inception to production within the platform architecture - Expert in MLflow SageMaker Kubeflow or Argo DVC Weights and Biases and other relevant platforms - Strong software engineering abilities in Python JavaScript TypeScript - Expert in AWS services and containerization technologies like Docker and Kubernetes - Experience with LLMOps frameworks such as LlamaIndex and LangChain - Ability to collaborate effectively with engineering design product and science teams - Strong written and verbal communication skills for reporting and documentation - Minimum of 4 years in ML AI operations engineering roles - Proven track record of deploying algorithms and machine learning models into production environments - Demonstrated ability to work closely with cross-functional teams particularly data scientists 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 AstraZeneca is where creativity meets critical thinking We embrace technology to reimagine healthcare s future by predicting preventing and treating conditions more effectively Our inclusive approach fosters collaboration internally and externally to share diverse perspectives We empower our teams with trust and space to explore innovative solutions that redefine patient experiences across their journey Join us as we drive change that benefits both business and patients Ready to make an impact Apply now to join our journey towards transforming healthcare Date Posted 18-Jul-2025 Closing Date 31-Jul-2025 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