Sr. AI / ML Research Engineer-1

Trane Technologies
Bengaluru
Workplace: HybridFull timeFunction: Research & Scientific (R&D)Education: phdSkills: ["Communication","Collaboration"]

Develop physics-based AI capabilities for fluid and thermal (CFD/multi-physics) simulation, translating physics-informed neural networks and related scientific ML methods into production-ready workflows. Build surrogate and reduced-order models to improve simulation speed and fidelity, create end-to-end training/validation/benchmarking pipelines, and run simulation campaigns with design of experiments. Collaborate across research, software, and product teams to deploy scalable tools, using solvers like ANSYS Fluent and OpenFOAM.

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FursaFursa
Trane Technologies
Trane Technologies
4 days ago

Sr. AI / ML Research Engineer-1

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Last checked: 4 hours agoStatus: Live

Job Summary

Develop physics-based AI capabilities for fluid and thermal (CFD/multi-physics) simulation, translating physics-informed neural networks and related scientific ML methods into production-ready workflows. Build surrogate and reduced-order models to improve simulation speed and fidelity, create end-to-end training/validation/benchmarking pipelines, and run simulation campaigns with design of experiments. Collaborate across research, software, and product teams to deploy scalable tools, using solvers like ANSYS Fluent and OpenFOAM.
Location: Bengaluru
Workplace: Hybrid
Employment Type: Full time
Job Function: Research & Scientific (R&D)
Seniority: Mid level

Key Responsibilities

  • •Develop and apply AI/ML methods for CFD and multi-physics simulation problems in fluid flow, heat transfer, turbulence, and thermal management.
  • •Build physics-informed neural networks and related scientific ML methods for forward/inverse modeling, parameter estimation, data assimilation, and hybrid simulation workflows.
  • •Create surrogate and reduced-order models to accelerate high-fidelity simulation while preserving engineering accuracy.
  • •Apply design of experiments to simulation campaigns, data generation, sensitivity analysis, and efficient exploration of high-dimensional design spaces.
  • •Integrate with simulation data from solvers (ANSYS Fluent, STAR-CCM+, OpenFOAM, Moldflow), design scientific ML training/validation/benchmarking, and collaborate to deploy results into scalable engineering workflows.

Key Requirements

  • •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 (data preparation, training, evaluation, hyperparameter tuning, and model deployment) and working in Linux/HPC environments (GPU-based training desirable).
Experience:Computational fluid dynamicsScientific computingPhysics-informed machine learningHPCDigital engineering
Education:PhD / Doctorate in Mechanical Engineering; Aerospace Engineering; Applied Mathematics; Computer Science; Physics
Skills:CommunicationCollaboration
Tech Stack:PythonPyTorchTensorFlowJAXLinuxGPUHPCANSYS FluentSTAR-CCM+OpenFOAMMoldflowCFDPhysics-informed neural networksSurrogate modelingReduced-order modelingNeural operatorsDesign of experiments

Company Brief

Trane Technologies
Designs and manufactures HVAC and climate solutions for commercial, industrial, and residential buildings. Focuses on heating, cooling, ventilation, and building efficiency systems under brands like Trane and Thermo King.
Industry: Manufacturing
Company Size: Enterprise (1,001+ employees)
Revenue: USD 10B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Dublin, Ireland
Founded: 2013
WebsiteLinkedIn