Implement Content & Documentation Tooling: Assist in building tools and scripts to convert, generate, or publish documentation artifacts (e.g., Markdown/MDX pipelines, changelogs, and release summaries from Jira/PR data).
Apply AI to Developer Tooling: Explore using LLMs and agentic scripts for practical site health tasks, such as flagging stale screenshots or enhancing doc indexing and retrieval for AI assistants.
Collaborate & Document: Work closely with your mentor and docs engineers, communicate progress in weekly syncs, and present your accomplishments at the end-of-internship Showcase.
What you'll learn
CI/CD & Developer Productivity: Practical experience building GitHub workflows, PR bots, and test automation pipelines in a large-scale engineering environment.
Modern Documentation Engineering: Hands-on experience with modern documentation frameworks (Markdown, MDX, static site generators) and API documentation lifecycles.
Pragmatic AI & LLM Automation: How to apply LLMs, scripting, and evaluation to automate real-world maintenance tasks.
Collaborative Software Engineering: Working in an async-first culture using Git, code reviews, Slack, and agile delivery practices.
Program Structure
Phase I (Month 1) — Onboarding & Foundation: Learn the platform, toolchains, and repos. Co-create an Individual Learning Plan with your mentor and complete your first guided tickets.
Phase II (Months 2–5) — Core Project Delivery: Take ownership of scoped automation projects (e.g., CI testing of doc snippets, PR review gating, or generator scripts) with ongoing guidance and weekly 1:1 check-ins.
Phase III (Month 6) — Refinement, Handoff & Showcase: Finalize deliverables, write clean documentation for the team to maintain your work, and present your accomplishments at an Intern Showcase.
Qualifications
Recent graduate or completed Bachelor’s/Master’s degree in Computer Science, Software Engineering, Data Science, or a related field (or equivalent practical project experience).
Solid foundational programming skills in Python and comfort with scripting or data parsing.
Familiarity with Git and GitHub workflows (branching, pull requests, code reviews).
Basic exposure to or enthusiasm for CI/CD concepts (e.g., GitHub Actions) and web/documentation formats (Markdown, HTML/CSS, or JavaScript/TypeScript).
Curiosity and eagerness to experiment with LLM APIs for developer productivity.
Strong written communication skills and an organized, problem-solving mindset.
Nice to Have
Experience writing GitHub Actions or automating developer workflows.
Prior experience with static site generators (Docusaurus, MkDocs, Next.js, etc.) or MDX.
Familiarity with running automated tests or linting tools in CI pipelines.
Personal or academic projects integrating LLM APIs (e.g., OpenAI, Anthropic, or open-source models).
The talent and dedication of our employees are at the core of DataRobot’s journey to be an iconic company. We strive to attract and retain the best talent by providing competitive pay and benefits with our employees’ well-being at the core. Here’s what your benefits package may include depending on your location and local legal requirements: Medical, Dental & Vision Insurance, Flexible Time Off Program, Paid Holidays, Paid Parental Leave, Global Employee Assistance Program (EAP) and more!
DataRobot Operating Principles
Wow Our Customers
Set High Standards
Be Better Than Yesterday
Be Rigorous
Assume Positive Intent
Have the Tough Conversations
Be Better Together
Debate, Decide, Commit
Deliver Results
Overcommunicate
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DataRobot is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. DataRobot is committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. Please see the United States Department of Labor’s EEO poster and EEO poster supplement for additional information.
Use of Artificial Intelligence in Our Hiring Process
DataRobot uses approved AI-powered tools to support the hiring process in selected regions. These tools may assist in writing job descriptions, reviewing applications, assessing qualifications, and evaluating candidate materials. All decisions regarding applications are made by members of the DataRobot team.
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