Senior Machine Learning Engineer

What you will doLet’s do this. Let’s change the world. In this vital role you will be part of the technical/engineering team, developing data flow pipelines to extract, transform, and load data from various data sources in various data formats to the enterprise data lake and data warehouse system in three regions in AWS. You will provide data analytics and predictive analysis to business users. We look for people who can work in a team, are able to mentor junior engineers, are curious to learn, and can develop data engineering and machine learning engineering solutions in a fast-moving environment.Be a key team member assisting in the design and development of the data pipeline for the Global Data and Analytics team.Work with Data Scientists to perform statistical analysis and model fine-tuning using test results; train and retrain systems when necessary.Work with Data Scientists to analyze common features across use cases; define reusable features in feature tables.Ensure consistent feature engineering between training and model serving.Automate model monitoring, model retraining, and model deployment processes based on business requirements.Adhere to best practices for coding, testing, and designing reusable code/components.Able to explore new tools and technologies that will help to improve ETL platform performance and machine learning operations.Participate in sprint planning meetings and provide estimations on technical implementation; collaborate and communicate effectively with the product team.Mentor junior data/machine learning engineers.What we expect of youWe are all different, yet we all use our unique contributions to serve patients. The professional we seek will have these qualifications:Basic Qualifications:Doctorate degreeOR Master’s degree and 3+ years of Information Systems experienceOR Bachelor’s degree and 5+ years of Information Systems experienceOR Associate’s degree and 10+ years of Information Systems experienceOR High school diploma / GED and 12+ years of Information Systems experiencePreferred Qualifications:Ability to write robust code in Python, Java, or R.Outstanding analytical and problem-solving skills; ability to learn quickly and detail-oriented.Familiar with PySpark data frame and data processing libraries, machine learning frameworks (like TensorFlow, Keras, or PyTorch), and other machine learning libraries.Familiar with the Machine Learning life cycle; able to implement feature store, MLflow, model registry, model deployment, model serving, and model monitoring.Experience with machine learning operations.Deep knowledge of math, probability, statistics, and algorithms.Experience with data modeling for both OLAP and OLTP databases; hands-on experience with SQL, especially SparkSQL performance tuning.Experience with software DevOps CI/CD tools, such as GitLab.Experience with Docker containers and Kubernetes container orchestration.Experience with Apache Airflow and Apache Spark; Spark performance tuning.Experience with the Pharmaceutical industry, commercial operations.Excellent communication skills and ability to work in a team.What you can expect of usAs we work to develop treatments that take care of others, we also work to care for our teammates’ professional and personal growth and well-being.In addition to the base salary, Amgen offers a Total Rewards Plan comprising health and welfare plans for staff and eligible dependents, financial plans with opportunities to save towards retirement or other goals, work/life balance, and career development opportunities including: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 and bi-annual company-wide shutdowns.Flexible work models, including remote work arrangements, where possible.

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