Remote ML Engineering Intern: Tools & AI Agents

Workiva; United States; Remote; USD 45,000 - 65,000; Part time

Benefits offered by this job

401(k) participation and match

Paid sick leave

Opportunity for additional internship季

Job summary

Workiva is offering a remote internship focused on building tools and libraries to support machine learning model development and deployment. You will prototype new tooling, integrate ML workflows, and contribute to AI agents that automate data processing tasks.

Ideal candidates are pursuing a degree in a relevant field, with solid programming skills and familiarity with Docker, Kubernetes, AWS, and REST APIs. Collaboration across distributed teams is expected.

Qualifications

• Pursuing a bachelor’s degree or higher in a relevant field.
• Solid programming skills.
• Basic experience with Git.
• Work effectively in a geographically distributed team.
• Strong communication and organizational skills.
• Familiarity with data science lifecycle and basic ML concepts.
• Experience with Docker and Kubernetes.
• Knowledge of AWS.
• Proficiency with Python and/or Go.
• Familiarity with REST APIs.

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 supervision.
• Help integrate tools like LlamaIndex and LlamaParse into workflows.
• Assist in building and deploying AI Agents to automate data processing and analysis tasks.
• Participate in code reviews.
• Implement and update tests (unit, integration).
• Track tasks and updates using internal tools.
• Work in an Agile development environment with teammates.

Skills

Programming skills

Communication skills

Agile development

REST APIs

Education

Bachelor’s degree or higher in Statistics, Mathematics, Computer Science, Physics, Electrical Engineering, or related field

Tools

Docker

Kubernetes

Git

AWS

Job description

Workiva is offering a remote internship focused on building tools and libraries to support machine learning model development and deployment. You will prototype new tooling, integrate ML workflows, and contribute to AI agents that automate data processing tasks.

Ideal candidates are pursuing a degree in a relevant field, with solid programming skills and familiarity with Docker, Kubernetes, AWS, and REST APIs. Collaboration across distributed teams is expected.