Sr. AI / ML Research Engineer-2

Location: Bangalore, Karnataka, India; onsite Monday through Thursday, with the option to choose the work location on Fridays

Company

hirify.global develops sustainable and efficient climate solutions for buildings, homes, and transportation through businesses including Trane and Thermo King.

What you will do

• Develop and apply AI/ML methods for CFD and multiphysics simulations involving fluid flow, heat transfer, turbulence, and thermal management.
• Build physics-informed neural networks for forward and inverse modeling, parameter estimation, data assimilation, and hybrid simulation workflows.
• Create surrogate and reduced-order models that accelerate high-fidelity simulations while preserving engineering accuracy.
• Design simulation campaigns, data-generation strategies, sensitivity analyses, and high-dimensional design-space exploration using Design of Experiments.
• Build training, validation, and benchmarking workflows using simulated and experimental datasets.
• Collaborate with domain experts, software engineers, product teams, vendors, and technology providers to transition research into scalable engineering tools.

Requirements

• PhD or MTech in mechanical engineering, aerospace engineering, applied mathematics, computer science, physics, or a related field with strong CFD or computational science expertise.
• Strong knowledge of computational fluid dynamics, PDE numerical methods, turbulence modeling, and heat transfer.
• Demonstrated experience applying physics-informed neural networks or related scientific ML methods to engineering or scientific computing problems.
• Strong Python programming skills and experience with PyTorch, TensorFlow, or JAX.
• Experience with end-to-end ML workflows, including data preparation, training, evaluation, hyperparameter tuning, and deployment.
• Understanding of model verification, validation, uncertainty, and physical consistency in engineering applications.

Nice to have

• Experience with neural operators, graph neural networks, geometric deep learning, differentiable simulation, or hybrid physics-ML modeling.
• Experience integrating AI models with CFD solvers, optimization frameworks, or digital twin platforms.
• Knowledge of Bayesian optimization, inverse design, control, geometry and mesh pipelines, simulation automation, or workflow orchestration.
• Experience with ANSYS Fluent, STAR-CCM+, OpenFOAM, Moldflow, or similar simulation platforms.
• Publications, patents, or production deployments in scientific ML, CFD, or physics-based AI.

Culture & Benefits

• Work on advanced AI for high-impact engineering and sustainable climate systems.
• Comprehensive benefits and employee programs.
• Cross-functional collaboration across research, engineering, and product teams.
• Equal opportunity employment.