Location
Bengaluru
Work Mode
In Office
Duration
undefined months
Stipend
₹0/mo
Start Date
Immediately
Openings
1 positions
Type
Full-time
Category
Machine Learning
About the Internship
Trane Technologies is hiring for Sr. AI / ML Research Engineer-1 in Bengaluru. This opening was published by Trane Technologies on their official careers board (Workday) on 27 August 2026 and was confirmed live on 14 September 2026.
Job details
• Company: Trane Technologies
• Role: Sr. AI / ML…
About Trane Technologies
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, and through our businesses including Trane® and Thermo King…
See all Trane Technologiesinternships →BengaluruVerified employer1 opening
Apply to Trane Technologies →Skills Required
PythonMachine LearningDeep LearningLinuxCommunicationANSYSTensorFlowPyTorch
Perks
Where is the work:Monday to Thursday, work onsite with your colleagues. Fridays, choose your work location, balancing what your work requires.Sr. AI / ML Research EngineerDescription - ExternalAt Trane Technologies and through our businesses including Trane and Thermo King, we create innovative climate solutions for buildings, homes, and transportation that challenge what’s possible for a sustainable world. We’re a team that dares to look at the world’s challenges and see impactful possibilities. We believe in a better future when we uplift others and enable our people to thrive at work and at home. We boldly go.We are seeking a Sr. AI / ML Research Engineer to help build next-generation physics-based AI capabilities for fluid and thermal systems. This role is ideal for a candidate who combines deep expertise in computational fluid dynamics, scientific computing, and modern machine learning to accelerate simulation, design optimization, and digital engineering workflows.The ideal candidate will bring hands-on experience applying physics-informed neural networks, neural operators, surrogate modeling, reduced-order modeling, and related scientific ML methods to real engineering problems. They will work across research and product teams to translate advanced methods into robust, production-oriented solutions that improve simulation speed, fidelity, and decision-making.
₹0/month
Stipend · months
Openings1 positions
Applicants0 applied
ModeIn Office
CategoryMachine Learning
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