Sr Machine Learning Engineer

Role Summary

Senior Machine Learning Engineer at Amgen. In this role you will build and scale machine learning models from development to production, applying ML and operations expertise to create efficient pipelines. You will collaborate with data scientists, engineers, and product teams to deliver ML solutions, leveraging cloud platforms and MLOps practices. You will help advance Amgen's mission to serve patients by delivering reliable, data-driven medicines.

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.
• Stay updated with the latest trends and advancements.

Qualifications

• Doctorate degree
• Master’s degree and 2 years of Computer Science experience
• Bachelor’s degree and 4 years of Computer Science experience
• Associate’s degree and 8 years of Computer Science experience
• High school diploma / GED and 10 years of Computer Science experience
• Preferred Qualifications: Certifications on GenAI/ML platforms (AWS AI, Azure AI Engineer, Google Cloud ML, etc.) are a plus.

Skills

• 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)
• Outstanding analytical and problem-solving skills; Ability to learn quickly; Good communication and interpersonal skills
• 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
• Experience in analyzing time-series data for forecasting and trend analysis
• Soft skills: Excellent analytical and troubleshooting skills; Strong verbal and written communication skills; Ability to work effectively with global, virtual teams; High degree of initiative and self-motivation; Ability to manage multiple priorities successfully; Team-oriented with a focus on achieving team goals; Ability to learn quickly, be organized and detail oriented; Strong presentation and public speaking skills

Education

• Doctorate degree
• Master’s degree
• Bachelor’s degree
• Associate’s degree
• High school diploma / GED