Machine Learning Engineer

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 such as AWS, GCP, or Azure for ML model development and deployment
• Implement DevOps and 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 engineers and product teams to deliver scalable ML solutions

Requirements

• Solid foundation in machine learning algorithms and techniques
• Experience with MLOps tools such as MLflow, Kubeflow, or Airflow
• Proficiency with DevOps tools including Docker, Kubernetes, and CI/CD
• Strong proficiency in Python and relevant ML libraries like TensorFlow, PyTorch, or Scikit-learn
• Master's degree with 5+ years of experience in Computer Science, IT, or a related field, OR a Bachelor's degree with 7-9+ years of experience

Preferred Qualifications

• Experience with big data technologies such as Spark or Hadoop
• Knowledge of NLP techniques for text analysis and sentiment analysis
• Experience with data engineering and pipeline development
• Experience in statistical techniques, hypothesis testing, and time-series forecasting
• Certifications on GenAI or ML platforms (e.g., AWS AI, Azure AI Engineer, Google Cloud ML)

About the Company

Amgen harnesses the best of biology and technology to fight the world’s toughest diseases and make people’s lives easier, fuller, and longer. As a biotechnology pioneer, we discover, develop, and deliver innovative medicines to help millions of patients worldwide.