Sr. AI / ML Research Engineer-2

Company: Trane Technologies

Location: Bangalore, Karnataka

Type: Full-time

Posted: 2026-07-20

About this role

Be a part of our mission! As a world leader in creating comfortable, sustainable, and efficient climate solutions for buildings, homes and transportation, it's our responsibility to put the planet first. For us at [Trane Technologies](https://www.tranetechnologies.com/), and through our businesses including [Trane®](http://www.trane.com/index.html) and [Thermo King](http://www.thermoking.com/na/en.html),  sustainability is not just how we do business—it is our business.  Do you dare to look at the world's challenges and see impactful possibilities?  Do you want to contribute to making a better future?  If the answer is yes, we invite you to consider joining us in boldly challenging what's possible for a sustainable world.

Learn about our [benefits](http://careers.tranetechnologies.com/global/en/benefits) designed for you to Thrive at work and at home.

We boldly go.

Where is the work:

Monday to Thursday, work onsite with your colleagues. Fridays, choose your work location, balancing what your work requires.

What's in it for you:
Be a part of our mission!

As a world leader in creating comfortable, sustainable, and efficient environments, it is our responsibility to put the planet first. For us at Trane Technologies, sustainability is not just how we do business—it is our business. If you want to apply advanced AI to high-impact engineering systems and help define the future of physics-based product development, we invite you to join us.

What you will do:

·        Develop and apply AI/ML methods for CFD and multi-physics simulation problems, especially in fluid flow, heat transfer, turbulence, and system-level thermal management.

·        Build physics-informed neural networks and related scientific ML approaches for forward modeling, inverse problems, parameter estimation, data assimilation, and hybrid simulation workflows.

·        Create surrogate and reduced-order models that accelerate high-fidelity simulation while preserving engineering a...

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