CDNA_ML Engineer Data Science Enablement

HOW MIGHT YOU DEFY IMAGINATION
If you feel like youre part of something bigger, its because you are At Amgen, our shared mission?to serve patients?drives all that we do It is key to our becoming one of the worlds leading biotechnology companies We are global collaborators who achieve together?researching, manufacturing, and delivering ever-better products that reach over 10 million patients worldwide Its time for a career you can be proud of Live | What you will do Build, test, and maintain reusable components for ML pipelines and data science use cases in collaboration with senior engineers and data scientists Develop model tracking, versioning, and deployment workflows using MLflow and Databricks Support data scientists across teams with infrastructure needs, connector usage, and dataset preparation Help prototype and deploy internal tools (e-g, Streamlit apps) to visualize model results or enable user interactions Follow engineering best practices around version control, documentation, and testing in shared repositories Collaborate with enterprise engineering and data platform teams to ensure compliance with cloud architecture, data privacy, and governance standards Thrive | What you can expect As we work to develop treatments that take care of others, we also work to care for our teammatesprofessional and personal growth and well-being Basic Qualifications Bachelors or Masters in Computer Science, Data Engineering, or related technical field 35 years of experience in ML engineering, data engineering, or DevOps supporting ML pipelines Proficiency in Python and SQL, with working knowledge of Databricks, MLflow, and AWS (S3, EC2, Lambda) Experience supporting model deployment, monitoring, and packaging workflows Ability to document work clearly and collaborate effectively with cross-functional teams Preferred Qualifications Familiarity with vector stores, embedding pipelines, or RAG-style use cases Experience developing or supporting Streamlit or Dash-based apps for data products Working knowledge of Git-based workflows, containerization, and CI/CD pipelines Passion for enabling data science teams and driving engineering quality