About this role
Amgen is seeking a highly skilled Machine Learning Engineer with a strong MLOps background to join the AI & Data Science department. This role focuses on building and scaling machine learning models from development to production, ensuring efficient and reliable ML pipelines. Responsibilities include collaborating with data scientists to develop, train, and evaluate models, building MLOps pipelines (data ingestion, feature engineering, deployment, monitoring), and leveraging cloud platforms like AWS, GCP, and Azure. The engineer will implement DevOps/MLOps best practices to automate workflows, conduct A/B testing, and optimize model performance. Required qualifications include a Master’s degree with 5+ years of experience or a Bachelor’s degree with 7-9+ years of experience in Computer Science, IT, or a related field. Candidates must possess a solid foundation in ML algorithms, proficiency in Python and ML libraries (TensorFlow, PyTorch, Scikit-learn), and experience with MLOps/DevOps tools (MLflow, Kubeflow, Airflow, Docker, Kubernetes). Preferred qualifications include experience with big data technologies (Spark, Hadoop), data engineering, statistical techniques, NLP, and time-series forecasting. Certifications on GenAI/ML platforms are considered a plus. The role requires excellent analytical, problem-solving, and communication skills, with the ability to work effectively in global, virtual teams.