Summer 2027 Intern - Machine Learning Engineering
Workiva
- Location
- Ames, United States
- Work style
- On-site
- Job type
- Part time, Internship
- Posted
- Oct 27
- 1 day ago
Career path
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About the company
Workiva
Computer software · 1,001 to 5,000 employees
Workiva is the platform designed to bring confidence, control, and a competitive edge to the world’s most complex organizations. Our AI-powered platform unifies finance, risk, and sustainability on a single, secure foundation—ensuring data is trusted, traceable, and ready to act on. With an unbroken path from source to output, leaders gain confidence in their numbers, visibility into current and emerging risks, and the ability to move with speed and precision in a constantly changing world. At Workiva, you’ll bring technology to market that executives, boards, and regulators depend on. The work you do here helps organizations navigate uncertainty, maintain trust, and make decisions that stand up to scrutiny. If you’re energized by meaningful challenges, inspired by collaborative teams, and motivated to help organizations turn uncertainty into advantage, we’d love to meet you.
What you'll do
- Participate in discovery, requirements gathering, and prototyping of new tools and libraries
- Implement tooling and features to support machine learning model development and deployment
- 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
- Implement and update tests (unit, integration)
What you need
- Currently pursuing a bachelor’s degree or higher in a listed field or related field of study
- Possess solid programming skills
- Basic experience with source control systems such as Git
- Work effectively within a geographically distributed team (preferred)
- Demonstrate strong communication and organizational skills (preferred)
- Familiarity with the data science lifecycle and basic machine learning concepts (preferred)
- Experience with containerization tools such as Docker and Kubernetes (preferred)
- Knowledge of cloud platforms such as AWS (preferred)
- Education: a bachelor's degree or a postgraduate degree
Key skills
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Perks
- 401(k) participation and match
- Paid sick leave
- additional internship seasons
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