ML Engineer Intern — BioTech Data & AI for Patients

Amgen SA; United States; Remote; USD 101,254,000 - 118,198,000; Full time

Job summary

Amgen invites applicants for a Grad Intern – Machine Learning Engineer in Technology, AI & Data (Summer 2027). You will help design data pipelines, ingest data from multiple sources, and collaborate with data scientists to build models and dashboards.

Ideal candidates are pursuing an MBA, Master’s, PharmD or PhD, with foundational Python/R skills, cloud familiarity (AWS/GCP/Azure), and an interest in NLP or time-series modeling.

Qualifications

• 18 years or older
• 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 and completion of the first year before the internship starts

Responsibilities

• Design, develop, and test scalable data pipelines for ingestion and transformation into data lakes and warehouses
• Collaborate with data engineers and scientists to clean, analyze, and visualize structured and unstructured data
• Support model training, evaluation, and deployment workflows
• Explore pharmaceutical datasets for data-driven insights and inform stakeholders with visualizations
• Learn and apply ML techniques, hypothesis testing, and statistical modeling
• Contribute to documentation of processes, models, and tools; participate in agile ceremonies

Skills

Python

R

Machine learning

Data analysis

Pandas

NumPy

Matplotlib/Seaborn

scikit-learn/XGBoost

SQL

Git

Cloud platforms

AWS

GCP

Azure

Databricks

Apache Spark

Apache Airflow

NLP

Time-series analysis

SCRUM/Agile

Education

Bachelor's degree

MBA program

Master’s program

PharmD program

PhD program

Tools

Git

Databricks

Apache Spark

Apache Airflow

Job description

Amgen invites applicants for a Grad Intern – Machine Learning Engineer in Technology, AI & Data (Summer 2027). You will help design data pipelines, ingest data from multiple sources, and collaborate with data scientists to build models and dashboards.

Ideal candidates are pursuing an MBA, Master’s, PharmD or PhD, with foundational Python/R skills, cloud familiarity (AWS/GCP/Azure), and an interest in NLP or time-series modeling.