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AI Engineer Intern

Job in Owensboro, Daviess County, Kentucky, 42302, USA
Listing for: Union Home Mortgage
Full Time, Apprenticeship/Internship position
Listed on 2026-09-02
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 25000 - 30000 USD Yearly USD 25000.00 30000.00 YEAR
Job Description & How to Apply Below
Union Home Mortgage’s L.E.A.D Internship Program’s goal is to provide a fun, interesting, and real-world environment for our interns to Learn about the industry, be Educated by Sr. Leadership and their peers, Achieve their personal goals and Develop their skills and knowledge base. We pride ourselves in providing innovative programs for our interns in order for them to learn and grow they progress through their careers.

Some of the programs we offer include: shadowing, mentoring, professional development, group projects and we even take our interns on corporate outings! Our internship program gives students a chance to meet new people, gain more experience, and learn from the best in the business! Our interns are treated like full-time Partners who work 40 hours a week during the 3-month summer program, are compensated, and based out of headquarters in Strongsville, Ohio.

An AI Engineer Intern will support the research, development, and evaluation of artificial intelligence solutions designed to improve mortgage operations, including loan origination, servicing, workflow efficiency, and customer  this role, you will apply foundational knowledge of machine learning, neural networks, Transformer architectures, large language models (LLMs), retrieval-augmented generation (RAG), and agentic AI systems to real-world business challenges. Working alongside experienced engineers and business stakeholders, you will research technical approaches, develop prototypes, test and evaluate AI systems, and help determine where AI can meaningfully improve processes and reduce manual effort.

DUTIES & RESPONSIBILITIES Research & Develop AI Solutions – Explore and prototype AI/ML solutions that improve business processes and customer experiences

Automate Repetitive Tasks – Identify opportunities to apply AI and automation to reduce manual effort

Build & Improve AI Workflows – Assist in developing LLM, RAG, agentic, and traditional machine learning workflows

Test & Evaluate Solutions – Evaluate AI outputs for accuracy, reliability, performance, and appropriate business use Support Responsible AI – Assist with safeguards, testing, documentation, and human-in-the-loop processes

Collaborate Across Teams – Work with technical and business stakeholders to understand problems and develop appropriate solutions

Research Emerging Technology – Stay current with developments in AI, machine learning, LLMs, and related technologies and evaluate their potential application

Basic to intermediate programming proficiency in Python and familiarity with software development concepts

Foundational understanding of machine learning, including supervised/unsupervised learning, training and validation, loss functions, optimization, overfitting, generalization, and model evaluation

Foundational understanding of neural networks and deep learning, including layers, weights, activation functions, forward propagation, back propagation, and gradient-based learning

Ability to explain the fundamentals of Transformer architectures, including attention/self-attention, tokens, embeddings, context windows, and autoregressive generation

Understanding of tokenization and embeddings, including how text is represented for LLMs and how embeddings support semantic search and retrieval

Familiarity with large language models (LLMs), including pretraining, inference, prompting/context engineering, tool calling, model limitations, hallucinations, and evaluation

Familiarity with RAG, fine-tuning, and model adaptation, including the high-level differences between prompting, retrieval, and fine-tuning approaches

Interest in AI agents and agentic workflows, including tool use, state, memory, routing, and orchestration; exposure to Lang Graph, Lang Chain, or similar frameworks is a plus Exposure to AI/ML libraries or frameworks such as PyTorch, Tensor Flow, Hugging Face, scikit-learn, Num Py, or pandas is preferred

Strong analytical, problem-solving, communication, and technical research skills with the ability to explain how and why an AI system works, not simply how to use itEDUCATION & EXPERIENCE Currently pursuing a bachelor's or graduate degree in Computer Science,…
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