Grad Intern Machine Learning Engineer Amgens Technology & Medical Organizations; Summer

Join Amgens Mission of Serving Patients

At Amgen, if you feel like youre part of something bigger, its because you are. Our shared missionto serve patients living with serious illnesses drives all that we do.

Since 1980, weve helped pioneer the world of biotech in our fight against the worlds 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.

As a member of the Amgen team, youll help make a lasting impact on the lives of patients as we research, manufacture, and deliver innovative medicines to help people live longer, fuller happier lives.

Our award-winning culture is collaborative, innovative, and science based. If you have a passion for challenges and the opportunities that lay within them, youll thrive as part of the Amgen team. Join us and transform the lives of patients while transforming your career.

Lets do this. Lets change the world. 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

• 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

We are all different, yet we all use our unique contributions to serve patients. The passionate and driven individual we seek is exemplifies the following qualifications:

Amgen requires that all individuals applying for a grad internship or a co-op assignment at Amgen must meet the following criteria:

• 18 years or older
• Graduated with a bachelors degree from an accredited college or university
• Currently enrolled in an MBA program for an MBA internship OR a Masters program for a Masters 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 Masters OR Pharm D OR Ph.D. program before the internship starts

• In the process of completing the first year of a Masters 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, Num Py), visualization (e.g., matplotlib, seaborn), and machine learning (e.g., scikit-learn, XGBoost)
• Exposure to cloud platforms…