Machine Learning Engineer at Amgen

Description

Amgen is looking for a Machine Learning Engineer with a strong MLOps background to build and scale machine learning models. The role involves collaborating with data scientists, developing MLOps pipelines, leveraging cloud platforms like AWS, GCP, or Azure, implementing DevOps/MLOps best practices, and conducting A/B testing. The ideal candidate will have a solid understanding of machine learning algorithms, proficiency in Python and relevant ML libraries, and excellent analytical and communication skills.

Required Skills

machine learning algorithms and techniques
MLOps practices and tools (e.g., MLflow, Kubeflow, Airflow)
DevOps tools (e.g., Docker, Kubernetes, CI/CD)
Python and relevant ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn)

Additional Information

Required Previous Experiences: 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)
Preferred Qualifications: 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.

About Amgen

Amgen

life-saving medicinesThousand Oaks, California

Amgen discovers, develops, manufactures and delivers innovative medicines to fight some of the world’s toughest diseases. Harnessing the best of biology and technology, Amgen reaches millions of patients with its medicines, helping make people’s lives easier, fuller and longer.