AI Engineering Intern Summer 2027

Lennox International•Richardson, TX

1d•$23 - $25•Onsite

About The Position

As an Intern at Lennox, you will be a part of a team of innovative and knowledgeable industry professionals. You can expect to participate in impactful, developmental projects designed for your specific area of focus. This is approximately a 10 to 12-week program that will provide you with real work experiences to grow your career and provide exposure to business leaders throughout the company. Successful interns will have the potential opportunity of joining Lennox Full-Time upon graduation. Relocation and/or travel may be required for your position.

Requirements

Pursuing a Masters degree in a related field
Strong foundation in machine learning and data science, including regression, classification, and time series modeling.
Strong written and verbal communication
Proficiency in Python and data tools such as Pandas, NumPy, Scikit-learn, and SQL
Understanding of GenAI and LLMs, with interest in prompt engineering, agentic workflows, and tool integration
Ability to analyze structured and unstructured data, perform feature engineering, and build interpretable models.
Requires current enrollment in a Masters program.
Developing professional knowledge in the area of expertise.
Solid written and verbal communication skills.
Proficient in Microsoft Office.

Nice To Haves

Interest or desire to lead project teams
Well organized & detail oriented
Ability to work independent as well as part of a team
Passion for producing high quality work

Responsibilities

Collaborate on building agentic AI systems that automate diagnostics and decision-making in engineering workflows.
Develop and validate machine learning models for forecasting, quoting, and operational optimization.
Conduct data analysis and feature engineering using structured and unstructured enterprise datasets.
Contribute to LLM-based agent development, including prompt design, tool integration, and fallback orchestration.
Assist in deploying models and agents using cloud technologies and secure enterprise pipelines.
Participate in AI governance, ensuring models comply with data policies and learn from feedback.
Work cross-functionally with product, engineering, and business teams to deliver impactful solutions.