Associate Director, RDU IT - MLOps

Associate Director, RDU IT - MLOps Introduction to the role: The Associate Director, RDU IT - MLOps reports to the IT Director of Data Science and is a critical role in Alexion IT RDU organization. You will be a key member of our IT team and play a crucial role in developing and implementing innovative machine learning solutions for our business.

Your expertise in MLOps will be critical in designing, building, and deploying production-ready machine learning models at scale. Accountabilities: Leading the development and implementation of MLOps infrastructure and tools for machine learning models Collaborating with multi-functional teams to identify, prioritize and solve business problems using machine learning techniques Designing, developing and implementing production-grade machine learning models that meet business requirements Overseeing the training, testing, and validation of machine learning models Ensuring that machine learning models meet high-quality standards, including scalability, maintainability, and performance Design and implement efficient development environments and processes for ML applications.

Communicating with collaborators and senior management to provide updates on the progress of machine learning projects Developing assets, accelerators and thought capital for your practice by providing best in class framework and reusable components Developing and maintaining MLOps pipelines to automate machine learning workflows and integrating them with existing IT systems Integrating Generative AI models based solutions within the broader machine learning ecosystem, ensuring they adhere to ethical guidelines and serve the intended business purposes Implementing robust monitoring and governance mechanisms for Generative AI models based solutions to ensure they evolve in alignment with business needs and regulatory standards The duties of this role are generally conducted in an office environment. As is typical of an office-based role, employees must be able, with or without an accommodation to: use a computer; engage in communications via phone, video, and electronic messaging; engage in problem solving and non-linear thought, analysis, and dialogue; collaborate with others; maintain general availability during standard business hours.

Essential Skills/Experience: Bachelor's degree in Computer Science, Electrical Engineering, Mathematics, Statistics, or a related field 5+ years of experience in developing and deploying machine learning models in production environments Hands-on experience building production models with focus on data science operations including serverless architectures, Kubernetes, Docker/containerization, and model upkeep and maintenance Familiarity with API-based application architecture and API frameworks. Experience with CICD orchestration frameworks, such as GitHub Actions, Jenkins or Bitbucket pipelines.

Deep understanding of software development lifecycle and maintenance. Extensive experience with one or more orchestration tools (e.g Airflow, Flyte, Kubeflow) Experience working with MLOps tools like experiment tracking, model registry tools and feature stores (e.g MLFlow, Sagemaker, Azure) Strong programming skills in Python and experience with libraries such as Tensorflow, Keras, or PyTorch Proficiency in MLOps guidelines, including model training, testing, deployment, and monitoring Experience with cloud computing platforms, such as AWS, Azure or GCP Strong understanding of software engineering best practices and agile methodologies Strong understanding of data structures, algorithms, and machine learning techniques Excellent communication and collaboration skills with the ability to work in a cross-functional team environment Ability to work independently and determined with strong problem-solving skills Excellent communication and collaboration skills with the ability to partner well with business collaborators.

Desirable Skills/Experience : Experience in the pharmaceutical industry or related fields Advanced degree in Computer Science, Electrical Engineering, Mathematics, Statistics, or a related field Strong understanding of parallelization and asynchronous computation. Strong knowledge of data science techniques and tools, including statistical analysis, data visualization, and SQL Why AstraZeneca: Here, purpose and progress go hand in hand.

You will apply advanced AI in a passionate environment focused on people with unusual, serious conditions. You will work alongside colleagues who combine science, technology, and patient insight to solve hard problems.

Expect the agility of a biotech-minded team with the scale and stability to take big ideas into production, fast. We value kindness alongside ambition, put unexpected teams in the same room to spark bold thinking, and invest in your growth so you can stretch your capabilities while seeing your work translate to real-world outcomes.

Call to Action: If you are ready to define how Generative AI delivers meaningful impact at scale, step into this role and lead the work that moves patients, products, and possibilities forward!