Job Title: Associate Director, RDU IT - MLOps

Introduction to role:
Are you ready to lead the charge in transforming machine learning operations? As the Associate Director, RDU IT - MLOps, you'll report directly to the IT Director of Data Science and play a pivotal role in Alexion's IT RDU organization. Your mission? To develop and implement cutting-edge machine learning solutions that drive our business forward. Your expertise will be the cornerstone in designing, building, and deploying scalable, production-ready machine learning models. Are you up for the challenge?

Accountabilities:
- Lead the development and implementation of MLOps infrastructure and tools for machine learning models.
- Collaborate with multi-functional teams to identify, prioritize, and solve business problems using machine learning techniques.
- Design, develop, and implement production-grade machine learning models that meet business requirements.
- Oversee the training, testing, and validation of machine learning models.
- Ensure machine learning models meet high-quality standards, including scalability, maintainability, and performance.
- Design and implement efficient development environments and processes for ML applications.
- Communicate with collaborators and senior management to share updates on the progress of machine learning projects.
- Develop assets, accelerators, and thought capital for your practice by providing best-in-class frameworks and reusable components.
- Develop and maintain MLOps pipelines to automate machine learning workflows and integrate them with existing IT systems.
- Integrate Generative AI models within the broader machine learning ecosystem, ensuring alignment with ethical guidelines and business purposes.
- Implement robust monitoring and governance mechanisms for Generative AI models to ensure alignment with business needs and regulatory standards.

Essential Skills/Experience:
- Bachelor's degree in Computer Science, Electrical Engineering, Mathematics, Statistics, or a related field.
- 4+ years of experience in developing and deploying machine learning models in production environments.
- Hands-on experience building production models with a 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.
- Proficient in software engineering procedures and agile techniques.
- Strong understanding of data structures, algorithms, and machine learning techniques.
- Excellent communication and collaboration skills with the ability to work in a multi-functional team environment.
- Ability to work independently and self-driven with strong problem-solving skills.
- Strong communication and collaboration skills, adept at partnering effectively 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.

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's Alexion division, you'll find yourself at the forefront of rare disease biopharma. Our commitment to transparency and ethics drives us to push scientific boundaries and translate complex biology into transformative medicines. With global reach and potent capabilities, we are shaping the future of rare disease treatment to address unmet needs. Here, you'll grow in an energizing culture that values innovation and connection. Empowered by tailored development programs, you'll align your growth with our mission to make a difference for patients worldwide.

Ready to make an impact? Apply now to join our team!

Date Posted

Closing Date

Alexion is proud to be an Equal Employment Opportunity and Affirmative Action employer. We are committed to fostering a culture of belonging where every single person can belong because of their uniqueness. The Company will not make decisions about employment, training, compensation, promotion, and other terms and conditions of employment based on race, color, religion, creed or lack thereof, sex, sexual orientation, age, ancestry, national origin, ethnicity, citizenship status, marital status, pregnancy, (including childbirth, breastfeeding, or related medical conditions), parental status (including adoption or surrogacy), military status, protected veteran status, disability, medical condition, gender identity or expression, genetic information, mental illness or other characteristics protected by law. Alexion provides reasonable accommodations to meet the needs of candidates and employees. To begin an interactive dialogue with Alexion regarding an accommodation, please contact accommodations@Alexion.com. Alexion participates in E-Verify.