Remote ML Engineering Intern: AI Tools & Deployment

Workiva; United States; Hybrid; USD 45,000 - 65,000; Full time

Benefits offered by this job

Paid sick leave

401(k) match

Remote internship option

Job summary

Workiva is seeking a Machine Learning Engineering Intern to join the Data Management and Analytics team, contributing to the ML lifecycle with hands-on experience in development, deployment, and monitoring of models.

You will gain experience with tools like LlamaIndex and LlamaParse, participate in code reviews, and collaborate in an Agile environment across distributed teams, with remote or hybrid options.

Qualifications

• Pursuing a bachelor’s degree or higher in Statistics, Mathematics, Computer Science, Physics, Electrical Engineering, or related field of study.
• Solid programming skills and basic experience with Git.

Responsibilities

• Participate in discovery, requirements gathering, and prototyping of new tools and libraries.
• Implement tooling and features to support ML model development and deployment under the direction of a full‑time Machine Learning Engineer.
• Help integrate tools such as LlamaIndex and LlamaParse into existing workflows.
• Assist in building and deploying AI Agents to automate data processing and analysis tasks.
• Participate in code reviews and implement/update tests (unit, integration).
• Track tasks and provide status updates using internal tools; work in an Agile development environment.

Skills

Python

Go

Git

REST APIs

Agile

Education

Bachelor's degree or higher in Statistics/Math/CS/Physics/EE or related field

Tools

Docker

Kubernetes

AWS

REST APIs

Job description

Workiva is seeking a Machine Learning Engineering Intern to join the Data Management and Analytics team, contributing to the ML lifecycle with hands-on experience in development, deployment, and monitoring of models.

You will gain experience with tools like LlamaIndex and LlamaParse, participate in code reviews, and collaborate in an Agile environment across distributed teams, with remote or hybrid options.