Lennox is looking to solve business and technical problems related to automating diagnostics and decision-making in engineering workflows, forecasting, quoting, and operational optimization through the development and deployment of agentic AI systems and machine learning models.
Requirements
- Strong foundation in machine learning and data science, including regression, classification, and time series modeling.
- 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.
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.
Other
- Pursuing a Masters degree in a related field
- Strong written and verbal communication
- Interest or desire to lead project teams
- Well organized & detail oriented
- Ability to work independent as well as part of a team
