Develop machine learning models related to equipment telemetry
Deploy ML/DL Models into cloud-based access for internal use
Design data pipelines to ingest, clean, and analyze sensor, operational, and service data
Continuously refine models based on real-world equipment performance
Design and build supportive AI tools for the service, operations, and engineering team
Translate engineering formulas, design rules, and constraints into reliable, user-friendly digital tools
Collaborate with engineers to ensure accuracy, usability, and maintainability
Leverage Agentic AI to operationalize the AI project development
Assist the AI/ML team in developing the AI digital twin
Provide knowledge and understanding of ML behaviors relative to AI digital twins
Support additional data and digital tool initiatives as required by the business
Evaluate new opportunities where advanced analytics can improve products, services, or operations
Contribute to long-term data strategy at ThermalWorks
Lead a team of junior developers in additional projects.

Degree in Computer Science, Engineering, Data Science, or a related technical field
Strong experience in Python and applied machine learning
Ability to translate engineering or operational problems into practical software tools
Strong collaboration skills across engineering, service, and business teams
Comfort working on multiple projects with varying stakeholders
Experience with predictive maintenance or industrial/physical systems
Familiarity with time-series data and sensor data analysis
Experience with web-based tools, APIs, or engineering calculation software
Knowledge of ML Ops, model deployment, and monitoring
Experience in manufacturing, industrial equipment, or engineering-driven organizations.

Machine Learning Engineer, AI

Key skills