ML Engineering Intern - AI Platform & R&D

100 Eli Lilly and Company; Indianapolis (IN); On-site; USD 77,000 - 94,000; Full time

Benefits offered by this job

Paid time off

Free parking

Lilly LIFE fitness center access

Subsidized housing

Job summary

Lilly in Indianapolis, Indiana, invites a Master’s student in CS/Engineering/Math to join its Advanced Intelligence team for a 10–12 week full-time internship. You will contribute to AI-enabled drug discovery platforms, develop scalable ML systems, and work under senior engineers to deliver production-ready code.

You will gain exposure to agent orchestration, model serving, data pipelines, and observability, while growing your technical depth in pharma R&D context.

Qualifications

• Pursuing a Master’s degree in CS/Engineering/Math with 2 years in undergrad or enrolled in a graduate program.
• Coursework or project experience in ML, distributed systems, data engineering, or software design.
• Familiar with cloud platforms (AWS/GCP/Azure) or containerization (Docker/Kubernetes).
• Available for 10–12 weeks full-time engagement May–Sept 2027.
• Authorized to work in the United States without sponsorship.

Responsibilities

• Contribute to design, implementation, and testing of platform capabilities in your domain.
• Build and ship features for an AIOS platform under mentor guidance.
• Write well-tested production-quality code following standards.
• Participate in code reviews, design discussions, and sprint ceremonies.
• Gain hands-on experience with agent orchestration, model serving, data pipelines and observability.

Skills

Machine learning

Distributed systems

Data engineering

Software design

Cloud platforms

Docker

Kubernetes

Git

Python

Go

Education

Master's degree in CS/Engineering/Math

Currently enrolled in graduate program

Tools

Docker

Kubernetes

Git

Job description

Lilly in Indianapolis, Indiana, invites a Master’s student in CS/Engineering/Math to join its Advanced Intelligence team for a 10–12 week full-time internship. You will contribute to AI-enabled drug discovery platforms, develop scalable ML systems, and work under senior engineers to deliver production-ready code.

You will gain exposure to agent orchestration, model serving, data pipelines, and observability, while growing your technical depth in pharma R&D context.