AI Engineering Intern Summer 2027

Lennox International•Richardson, TX

13d

About The Position

Lennox (NYSE: LII) is seeking an AI Engineering Intern for Summer 2027. Driven by 130 years of HVAC and refrigeration success, Lennox provides industry-leading climate-control solutions. Our culture emphasizes winning as a team, aiming for excellence, and delivering innovative, sustainable products and services. We foster a supportive environment where all employees feel heard and welcomed, offering opportunities for career development. As an intern, you will join a team of innovative professionals, participating in impactful, developmental projects. This approximately 10 to 12-week program offers real work experiences, exposure to business leaders, and potential for full-time employment upon graduation. Relocation and/or travel may be required.

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.