Amgen is looking to solve the problem of serving patients living with serious illnesses by developing and delivering innovative medicines, and this role is expected to contribute to this mission by building and scaling machine learning models from development to production.
Requirements
- Solid 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)
- Experience with big data technologies (e.g., Spark, Hadoop), and performance tuning in query and data processing
- Experience with data engineering and pipeline development
- Experience in statistical techniques and hypothesis testing, experience with regression analysis, clustering and classification
- Knowledge of NLP techniques for text analysis and sentiment analysis
Responsibilities
- 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 DevOps/MLOps best practices to automate ML workflows and improve efficiency.
- Develop and implement monitoring systems to track model performance and identify issues.
- Conduct A/B testing and experimentation to optimize model performance.
- Work closely with data scientists, engineers, and product teams to deliver ML solutions.
Other
- Doctorate degree
- Masters degree and 2 years of Computer Science experience
- Bachelors degree and 4 years of Computer Science experience
- Associates degree and 8 years of Computer Science experience
- High school diploma / GED and 10 years of Computer Science experience
- Excellent analytical and troubleshooting skills.
