Amgen Inc. is hiring a Machine Learning Engineer to develop and optimize the company's ML pipelines and architecture. In this role, you will play a pivotal part in building and scaling machine learning models from development to production.

What You'll Do

Collaborate with data scientists to develop, train, and evaluate machine learning models.
Build and maintain MLOps pipelines, including data ingestion, feature engineering, model training, deployment, and monitoring.
Leverage cloud platforms (AWS, GCP, Azure) for ML model development, training, and deployment.
Implement best practices to automate ML workflows and improve efficiency.
Conduct A/B testing and experimentation to optimize model performance.
Work closely with data scientists, engineers, and product teams to deliver ML solutions.
Contribute to the design, development, and implementation of data pipelines, ETL/ELT processes, and data integration solutions.
Take ownership of ML pipeline projects from inception to deployment, managing scope, timelines, and risks.
Ensure data quality and integrity through rigorous testing and monitoring.
Identify and resolve complex data-related challenges.
Adhere to data engineering best practices and standards.
Stay updated with the latest trends and advancements.

What We're Looking For

Strong foundation in machine learning algorithms and techniques.
Experience in MLOps practices and tools (e.g., MLflow, Kubeflow, Airflow).
Experience in DevOps tools (e.g., Docker, Kubernetes, CI/CD).
Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
Outstanding analytical and problem-solving skills with the ability to learn quickly.
Excellent communication and interpersonal skills.
Experience with data engineering and pipeline development.
Master’s degree in computer science or STEM majors with a minimum of 5 years of Information Systems experience OR Bachelor’s degree in computer science or STEM majors with a minimum of 7 years of Information Systems experience.

Nice to Have

Experience in statistical techniques and hypothesis testing, including regression analysis, clustering, and classification.
Knowledge of NLP techniques for text analysis and sentiment analysis.
Experience in analyzing time-series data for forecasting and trend analysis.
Experience with AWS, Azure, or Google Cloud.
Experience with the Databricks platform for data analytics and MLOps.
Any AWS Developer Certification.
Any Python and ML certification.
Databricks Certification.
Any SAFe Agile certification.