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Senior Machine Learning Engineer at Amgen. Join Amgen’s Mission of Serving Patients. In this vital role you will play a pivotal role in building and scaling our machine learning models from development to production. Your expertise in both machine learning and operations will be essential in creating efficient and reliable ML pipelines.
Job Responsibility
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
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)
Outstanding analytical and problem-solving skills
Ability to learn quickly
Good communication and interpersonal skills
Doctorate degree OR Master’s degree and 2 years of Computer Science experience OR Bachelor’s degree and 4 years of Computer Science experience OR Associate’s degree and 8 years of Computer Science experience OR High school diploma / GED and 10 years of Computer Science experience
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
Nice to have
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
Certifications on GenAI/ML platforms (AWS AI, Azure AI Engineer, Google Cloud ML, etc.) are a plus
What we offer
A comprehensive employee benefits package, including a Retirement and Savings Plan with generous company contributions, group medical, dental and vision coverage, life and disability insurance, and flexible spending accounts
A discretionary annual bonus program, or for field sales representatives, a sales-based incentive plan
Stock-based long-term incentives
Award-winning time-off plans
Flexible work models, including remote and hybrid work arrangements, where possible