United Airlines Internship 2026
United Airlines
Key Responsibilities
- Technical Collaboration & Prototyping: Work alongside senior Data Scientists and AI Engineers to rapidly prototype GenAI solutions, RAG pipelines, and intelligent document processing tools.
- Secure Development & Documentation: Write clean, secure, and well-documented code for experimental AI workloads to enable reusability and enterprise integration.
- Data Analysis & Model Evaluation: Perform exploratory data analysis and assist in evaluating model outputs for accuracy, context retention, and hallucination reduction.
- Technical Communication: Document research insights, present experimental results, and demonstrate prototypes to technical managers and team peers.
Skills & Eligibility
- Education: Bachelor’s or Master’s degree (ongoing or completed) in Engineering, Technology, Computer Science, Statistics, Operations Research, Industrial Engineering, Applied Mathematics, Economics, or a related field.
- Duration: Availability to commit to a minimum internship duration of 6 months .
- Programming & Data Analysis: High proficiency in Python and SQL , combined with solid hands-on experience using Pandas and NumPy.
- AI / ML Core Skills: Foundational knowledge in Machine Learning (Model Training/Validation, Neural Networks) and a demonstrated understanding of Large Language Models (LLMs), Prompt Engineering mechanics, and Retrieval-Augmented Generation (RAG) architectures.
- AI Safety & Security: Awareness of secure coding practices, enterprise data privacy, prompt injection vulnerabilities, and secure API handling.
- Communication: Strong verbal and written communication skills to clearly articulate technical concepts to technical leads and peers.
- Prior internship experience in Data Science, Software Engineering, Machine Learning, or Advanced Analytics.
- Familiarity with orchestration frameworks like LangChain or LlamaIndex , and experience with APIs from OpenAI, Anthropic Claude, or Google Gemini.
- Exposure to Agentic workflows, multi-agent collaboration, tool-calling architectures, and vector databases (ChromaDB, FAISS, Pinecone).
- Hands-on experience with Git, GitHub version control, and Jupyter Notebook environments.
- Demonstrated engagement in the AI community through personal projects, hackathons, or open-source GitHub contributions.
- Education: Bachelor’s or Master’s degree (ongoing or completed) in Engineering, Technology, Computer Science, Statistics, Operations Research, Industrial Engineering, Applied Mathematics, Economics, or a related field.
- Duration: Availability to commit to a minimum internship duration of 6 months .
- Programming & Data Analysis: High proficiency in Python and SQL , combined with solid hands-on experience using Pandas and NumPy.
- AI / ML Core Skills: Foundational knowledge in Machine Learning (Model Training/Validation, Neural Networks) and a demonstrated understanding of Large Language Models (LLMs), Prompt Engineering mechanics, and Retrieval-Augmented Generation (RAG) architectures.
- AI Safety & Security: Awareness of secure coding practices, enterprise data privacy, prompt injection vulnerabilities, and secure API handling.
- Communication: Strong verbal and written communication skills to clearly articulate technical concepts to technical leads and peers.
- Prior internship experience in Data Science, Software Engineering, Machine Learning, or Advanced Analytics.
- Familiarity with orchestration frameworks like LangChain or LlamaIndex , and experience with APIs from OpenAI, Anthropic Claude, or Google Gemini.
- Exposure to Agentic workflows, multi-agent collaboration, tool-calling architectures, and vector databases (ChromaDB, FAISS, Pinecone).
- Hands-on experience with Git, GitHub version control, and Jupyter Notebook environments.
- Demonstrated engagement in the AI community through personal projects, hackathons, or open-source GitHub contributions.
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