Intern for AI Engineering and Data Science

AURORA COOPERATIVE ELEVATOR COMPANY • Aurora, NE

3d • Hybrid

About The Position

Aurora Cooperative is a farmer owned agricultural cooperative headquartered in Aurora, Nebraska. We provide inputs and services that power farming operations seed, fertilizer, crop protection, animal nutrition, energy products and we operate grain elevators across our network. Our mission is to create value for our owners by offering top quality products, services, and expertise. Role Overview Join the Data Science team to help design, build, and ship AI powered solutions that improve how we serve our members and run the business. You won’t just be running experiments; you’ll contribute to production grade systems alongside experienced engineers. You’ll help us professionalize our AI operations by contributing to automated testing frameworks, deployment pipelines, and observability tools for applications like chatbots, RAG assistants, and text to SQL interfaces.

Requirements

• Pursuing a degree in Computer Science, Data Science, Engineering, Statistics, or a related field (or equivalent practical experience).
• Hands on Build Experience You have built at least one AI enabled application (e.g., chatbot, RAG system, agent) and can explain how it works.
• AI Native Workflow You are comfortable using AI coding assistants (Cursor, GitHub Copilot, Claude Code, etc.) to accelerate your development.
• Core Tech Stack Proficiency in Python and SQL. Comfort with REST APIs and Git version control.
• Problem Solving Ability to break down complex problems, debug systems, and learn new technologies quickly.

Nice To Haves

• Experience with LLM Evaluation Familiarity with frameworks or methods for evaluating the quality of LLM outputs (e.g., RAGAS, TruLens, or custom metrics).
• DevOps, CI, CD Exposure Understanding of continuous integration/deployment concepts, containerization (Docker), or automated testing.
• Cloud & Data Experience with Snowflake, Azure, or similar cloud data platforms.
• Vector Search Understanding of vector databases, embeddings, and semantic search concepts.
• Frontend Skills Ability to build quick prototypes using Streamlit or similar tools.

Responsibilities

• Build & Deploy AI Applications Help develop AI applications (chatbots, RAG knowledge assistants, text to SQL) and contribute to deployment and upgrade processes.
• Automate Testing & Evaluation Contribute to automated testing frameworks that evaluate model performance, retrieval accuracy (RAG), and agent decision making before production.
• Develop Retrieval Pipelines Help engineer retrieval systems including chunking strategies, metadata management, embedding generation, and vector database indexing.
• Monitor & Optimize Assist with monitoring for system performance, latency, errors, and costs. Help build dashboards to track user interactions and model behavior.
• Curate Knowledge Bases Help build and maintain domain specific knowledge bases (agronomy, grain, logistics) using automated pipelines.
• Data Engineering Work with internal systems and SQL databases (Snowflake) to feed data into AI models and process outputs.
• Collaborate & Communicate Work with data engineers and domain experts to identify high impact use cases and present technical findings to stakeholders.

Benefits

• Real World Impact Contribute code that real employees use to solve real agricultural problems.
• End to End Exposure See projects through from the “business case” phase to deployment and monitoring, with guidance from senior team members.
• Mentorship Work directly with experienced data scientists and engineers who will help you grow your technical and professional skills.
• Domain Knowledge Learn how AI is applied in the complex world of modern agriculture and supply chain logistics.

What This Job Offers

• Career Level: Intern
• Education Level: No Education Listed
• Number of Employees: 501-1,000 employees