Sr. AI ML Research Engineer-2

Be a part of our mission! As a world leader in creating comfortable sustainable and efficient climate solutions for buildings homes and transportation its our responsibility to put the planet first. For us at Trane Technologies and through our businesses including TraneandThermo King sustainability is not just how we do businessit is our business. Do you dare to look at the worlds 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 whats possible for a sustainable world.

Learn about our benefits designed for you to Thrive at work and at home.

We boldly go.

Where is the work:

Whats 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 businessit 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 accuracy.

Apply Design of Experiments methods to simulation campaigns data generation strategies sensitivity analysis and efficient exploration of high-dimensional design spaces.

Work with structured and unstructured simulation data from commercial and open-source solvers such as ANSYS Fluent STAR-CCM OpenFOAM Moldflow or similar platforms.

Design training validation and benchmarking workflows for scientific ML models using both simulated and experimental datasets.

Partner with domain experts software engineers and product teams to deploy research into usable tools and scalable engineering workflows.

Partner with external vendors and strategic technology providers to evaluate adapt and transition advanced AI/ML solutions into scalable in-house capabilities and engineering workflows.

Contribute to technical strategy in physics AI scientific machine learning model validation and engineering optimization.

Communicating results clearly to technical and non-technical stakeholders and support adoption across the organization.

What you will bring:

PhD or MTech in Mechanical Engineering Aerospace Engineering Applied Mathematics Computer Science Physics or a closely related field with strong emphasis on CFD or computational science.

Strong foundation in computational fluid dynamics numerical methods for PDEs turbulence modeling and heat transfer.

Demonstrated experience applying physics-informed neural networks or related methods to engineering or scientific computing problems.

Strong programming skills in Python and experience with scientific ML frameworks such as PyTorch TensorFlow or JAX.

Experience building end-to-end ML workflows including data preparation training evaluation hyperparameter tuning and model deployment.

Experience working in Linux and HPC environments including parallel computing and GPU-based training (desirable).

Strong understanding of model verification validation uncertainty and physical consistency in engineering applications.

Excellent communication and collaboration skills with the ability to work across research and engineering teams.

We offer competitive compensation and comprehensive benefits and programs. We are an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race color religion sex sexual orientation gender identity national origin pregnancy age marital status disability status as a protected veteran or any legally protected status.