Undergrad ML Engineer Intern: Build & Deploy Models

Amgen Inc. (IR); Thousand Oaks (CA); Hybrid; USD 33,000 - 47,000; Full time

Job summary

Amgen is seeking an Undergrad Intern in Machine Learning Engineering for Summer 2027. You will work with data engineers and scientists to clean, prepare, and analyze data, and help automate model training and deployment pipelines.

You’ll gain experience analyzing pharmaceutical datasets, building informative visualizations, and applying statistical methods while collaborating in an Agile environment. This internship is located in the United States.

Qualifications

• 18 years or older and enrolled in a full-time Bachelor’s degree program with a 3.0+ GPA.
• Degree concentration in IT, CS, Engineering, Business or related field.
• Biotech/healthcare industry exposure preferred.
• Proficient with Microsoft Word, Excel and PowerPoint.
• Foundational Python or R experience with data libraries (pandas, NumPy).
• Exposure to cloud platforms (AWS/GCP/Azure).
• Familiar with SQL and data querying from relational sources.

Responsibilities

• Clean, prepare, and analyze structured and unstructured data.
• Support model training, evaluation, and deployment pipelines.
• Explore pharmaceutical datasets for data-driven insights.
• Design visualizations and dashboards for internal stakeholders.
• Apply statistics including hypothesis testing, regression, and classification.
• Collaborate on implementing ML models in production environments.
• Document technical processes, models, and tools.

Skills

Python

R

SQL

Data analysis

Git

Education

Bachelor's degree (undergrad)

Tools

Databricks

Apache Spark

Apache Airflow

AWS/GCP/Azure

Job description

Amgen is seeking an Undergrad Intern in Machine Learning Engineering for Summer 2027. You will work with data engineers and scientists to clean, prepare, and analyze data, and help automate model training and deployment pipelines.

You’ll gain experience analyzing pharmaceutical datasets, building informative visualizations, and applying statistical methods while collaborating in an Agile environment. This internship is located in the United States.