Sr Machine Learning Engineer
Amgen
July 01, 2026
Remote friendly (United States)
United States
IT
Senior Machine Learning Engineer
Responsibilities:
- Collaborate with data scientists to develop, train, and evaluate machine learning models.
- Build and maintain MLOps pipelines (data ingestion, feature engineering, model training, deployment, monitoring).
- Leverage cloud platforms (AWS, GCP, Azure) for ML development, training, and deployment.
- Implement DevOps/MLOps best practices to automate ML workflows and improve efficiency.
- Develop monitoring systems to track model performance and identify issues.
- Conduct A/B testing and experimentation to optimize model performance.
- Work with data scientists, engineers, and product teams to deliver ML solutions.
- Stay updated with latest trends and advancements.
Must-Have Skills:
- Solid foundation in machine learning algorithms and techniques.
- Experience with MLOps tools (e.g., MLflow, Kubeflow, Airflow) and DevOps tools (e.g., Docker, Kubernetes, CI/CD).
- Proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
- Outstanding analytical/problem-solving skills; ability to learn quickly; good communication/interpersonal skills.
Good-to-Have Skills:
- Big data technologies (e.g., Spark, Hadoop) and performance tuning.
- Data engineering and pipeline development.
- Statistical techniques/hypothesis testing; regression, clustering, classification.
- NLP (text analysis, sentiment analysis).
- Time-series analysis for forecasting and trend analysis.
Basic Qualifications:
- Doctorate OR
- Master’s degree + 2 years Computer Science experience OR
- Bachelor’s degree + 4 years Computer Science experience OR
- Associate’s degree + 8 years Computer Science experience OR
- High school diploma/GED + 10 years Computer Science experience.
Preferred Qualifications:
- GenAI/ML platform certifications (AWS AI, Azure AI Engineer, Google Cloud ML, etc.)
Application Instructions:
- Apply via careers.amgen.com. No application deadline; applications accepted until a sufficient number of candidates are received or a candidate is selected.
Responsibilities:
- Collaborate with data scientists to develop, train, and evaluate machine learning models.
- Build and maintain MLOps pipelines (data ingestion, feature engineering, model training, deployment, monitoring).
- Leverage cloud platforms (AWS, GCP, Azure) for ML development, training, and deployment.
- Implement DevOps/MLOps best practices to automate ML workflows and improve efficiency.
- Develop monitoring systems to track model performance and identify issues.
- Conduct A/B testing and experimentation to optimize model performance.
- Work with data scientists, engineers, and product teams to deliver ML solutions.
- Stay updated with latest trends and advancements.
Must-Have Skills:
- Solid foundation in machine learning algorithms and techniques.
- Experience with MLOps tools (e.g., MLflow, Kubeflow, Airflow) and DevOps tools (e.g., Docker, Kubernetes, CI/CD).
- Proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
- Outstanding analytical/problem-solving skills; ability to learn quickly; good communication/interpersonal skills.
Good-to-Have Skills:
- Big data technologies (e.g., Spark, Hadoop) and performance tuning.
- Data engineering and pipeline development.
- Statistical techniques/hypothesis testing; regression, clustering, classification.
- NLP (text analysis, sentiment analysis).
- Time-series analysis for forecasting and trend analysis.
Basic Qualifications:
- Doctorate OR
- Master’s degree + 2 years Computer Science experience OR
- Bachelor’s degree + 4 years Computer Science experience OR
- Associate’s degree + 8 years Computer Science experience OR
- High school diploma/GED + 10 years Computer Science experience.
Preferred Qualifications:
- GenAI/ML platform certifications (AWS AI, Azure AI Engineer, Google Cloud ML, etc.)
Application Instructions:
- Apply via careers.amgen.com. No application deadline; applications accepted until a sufficient number of candidates are received or a candidate is selected.