AI Engineer Intern

Copart•Dallas, TX

About The Position

Copart, Inc. is a technology leader and the premier online vehicle auction platform globally, with over 200 facilities located across the world. Copart links vehicle sellers to more than 750,000 buyers in over 190 countries. We believe in providing an unmatched experience, every day and everywhere, driven by our people, processes, and technology. We are looking for a passionate AI Engineering Intern with a strong interest in Artificial Intelligence to work on the development of our next-generation, AI-driven applications for our global expansion. In this role, you will work closely with Product Managers, AI Architects, and Tech Leads to understand requirements, integrate advanced AI capabilities, and build/modify scalable full-stack applications.

Requirements

Bachelor’s degree or higher (or currently pursuing) in Computer Science, Artificial Intelligence, Engineering, or a highly quantitative field.
Hands-on experience or academic projects working with LLM APIs (OpenAI, Anthropic, Ollama, Hugging Face).
Familiarity with RAG (Retrieval-Augmented Generation) architectures and prompt engineering.
Understanding of vector databases (e.g., PGvector, Pinecone, Milvus, or Chroma).
Experience with Python for AI, machine learning, data processing, and backend development.
Familiarity with Python AI and machine learning libraries, including TensorFlow, PyTorch, scikit-learn, NumPy, and pandas.
Understanding of machine learning model development, training, validation, evaluation, and deployment workflows.
Experience working with Python frameworks and tools such as FastAPI, Flask, Jupyter, or similar technologies.
Familiarity with model-serving and inference technologies, such as TorchServe, TensorFlow Serving, ONNX, or similar platforms.
Understanding of REST APIs, asynchronous processing, background jobs, and event-driven architectures.
Familiarity with data preprocessing, feature engineering, dataset management, and model performance evaluation.
Strong experience with Spring Boot, Spring WebFlux (for reactive/streaming APIs), and MVC.
Solid understanding of Core Java, multithreaded programming, and asynchronous task execution (essential for managing AI model call latency).
Experience writing Unit tests using JUnit and mocking frameworks.
Excellent problem-solving skills and a strong mathematical/logical foundation.
Innovative drive and a passion for quick mastery of emerging AI technologies, frameworks, and tools.
Self-motivated, naturally curious, and able to thrive in a fast-paced, client-focused environment.
Skilled in technical writing, including documenting AI system architectures and data flows.

Nice To Haves

Experience with AI orchestration frameworks like LangChain, LlamaIndex, or Spring AI.
Familiarity with Python (the primary language for data science/AI scripting) in addition to Java.
Experience writing SQL and stored procedures.
Familiarity with relational databases (MySQL, PostgreSQL) and NoSQL databases.
Experience working with vector indexes, embeddings, and similarity search.
Familiarity with data pipelines, ETL processes, and distributed data processing.
Experience with Git, Maven, and CI/CD tools (Jenkins, GitHub Actions).
Familiarity with cloud platforms (AWS, Azure, or GCP) and Docker containers for deploying AI models/services.
Basic knowledge of Unix/Linux environments

Responsibilities

Design and implement features powered by Large Language Models (LLMs), Generative AI, and Machine Learning APIs into our core web applications.
Develop efficient, secure, and real-time applications, peer-review code, and document solutions within an agile-blended software environment.
Build and optimize conversational agents, Retrieval-Augmented Generation (RAG) pipelines, and prompt engineering workflows.
Communicate proactively with teammates, AI research, infrastructure, security, and QA teams to continuously improve processes and engineering excellence.
Write highly concurrent, multi-threaded Java backend services capable of handling real-time AI inference and data streaming.