Machine Learning Engineer Intern

## Join Amgen’s Mission of Serving Patients At Amgen, if you feel like you’re part of something bigger, it’s because you are. Our shared mission—to serve patients living with serious illnesses—drives all that we do. Since 1980, we’ve helped pioneer the world of biotech in our fight against the world’s toughest diseases. With our focus on four therapeutic areas –Oncology, Inflammation, General Medicine, and Rare Disease– we reach millions of patients each year. Amgen is advancing a broad and deep pipeline of medicines to treat cancer, heart disease, inflammatory conditions, rare diseases, and obesity and obesity-related conditions. ## What You Will Do During this internship, you will acquire the valuable hands-on skills and foundational experience needed to become a professional in your chosen field. This role requires you to assist in the design, development, and testing of scalable data pipelines for data ingestion and transformation from multiple data sources into enterprise data lakes and warehouses. Responsibilities may include: - Work closely with expert data engineers and scientists to clean, prepare, and analyze structured and unstructured data - Support the development and automation of model training, evaluation, and deployment pipelines - Help explore and analyze pharmaceutical commercial datasets for data-driven insights - Participate in the design of informative visualizations and dashboards for internal stakeholders - Learn and apply statistical techniques including hypothesis testing, regression, and classification - Collaborate with the team on implementing and monitoring ML models in production environments - Contribute to the documentation of technical processes, models, and tools. - Experiment with new tools and techniques in data engineering and ML operations (MLOps) - Participate in agile ceremonies such as sprint planning and retrospectives to understand team workflow ## Program Eligibility Requirements - Must be available to work a full-time schedule. - Expected continued enrollment in an accredited college or university following the internship program / co-op - Student must be located in the United States for the duration of the internship program - Must be available to accept and commit to future full-time employment by July 2028, if offered ## What We Expect of You Basic Qualifications: - 18 years or older - Graduated with a bachelor’s degree from an accredited college or university - Currently enrolled in an MBA program for an MBA internship OR a Master’s program for a Master’s internship OR a PharmD program for a PharmD internship OR Ph.D. for a PhD internship from an accredited college or university and completion of the first year of MBA OR Master’s OR Pharm D OR Ph.D. program before the internship startsPreferred Qualifications: - In the process of completing the first year of a Master’s program with concentration in Information Technology, Computer Science (e.g., CS, CPE, SE), Engineering, Business, or related field - 1 or more years relevant work experience - Biotechnology, pharmaceutical or health care industry experience - Intermediate knowledge of Microsoft Word, Excel and Power Point - Strong interpersonal, project management, analytical and quantitative skills - Demonstrated personal initiative, self-motivation, flexibility, adaptability and resourcefulness - Ability to operate independently, across functional lines, and with both internal and external customers - Foundational experience in Python or R, including use of libraries for data manipulation (e.g., pandas, NumPy), visualization (e.g., matplotlib, seaborn), and machine learning (e.g., scikit-learn, XGBoost) - Exposure to cloud platforms such as AWS, GCP, or Azure (coursework or personal projects) - Basic understanding of SQL and experience querying data from relational or big data sources - Interest or coursework in NLP, time-series analysis, or statistical modeling - Familiarity with version control tools (e.g., Git) and collaborative coding practices - Awareness of tools like Databricks, Apache Spark, or Apache Airflow is a plus - Strong communication skills to optimally share technical findings with diverse audiences