MDB Engineer

Key Responsibilities:

? Develop and maintain accurate refrigerant component/system models, ensuring

alignment with product requirements.

? Participate in the full lifecycle of refrigerant component calculation development in C#

or Python, including specification, design, implementation, unit testing, accuracy

assurance, integration with .NET APIs, and maintenance.

? Design, develop, and validate complex thermal models for refrigerant components, such

as heat exchangers, chillers, compressors, condensers, evaporators, and expansion

valves.

? Apply Model-Based Design (MBD) methodologies to develop, implement, and verify

real-time control systems for refrigeration systems and refrigerated display cabinets.

? Interpret simulation results to extract insights and inform design decisions.

? Collaborate with Product Owners and technical teams to troubleshoot and resolve

issues.

? Conduct model testing, calibration, and validation using experimental data.

? Work with global engineering design centers on challenging modeling problems,

promoting the use of simulation techniques to support design decisions.

? Demonstrate the ability to learn new modeling tools/inhouse tools quickly and apply

them effectively to solve complex engineering problems.

Qualifications:

o MS in Engineering, Data Analytics, or Physics, OR

o Ph.D. in Mechanical Engineering with specialization in Thermal and Fluid Science.

? Experience:

o 8+ years of relevant experience in thermal modeling or related fields.

? Mandatory Skills:

o Proficiency in C# /Python for model development.

o Strong understanding of HVAC&R systems, thermal fluid systems, and

thermodynamic cycles.

o Expertise in writing/solving equation-based models

o Knowledge of refrigerant components such as heat exchangers, chillers,

compressors, condensers, and evaporators.

Additional Skills (Preferred):

o Experience in Python, .NET, Fortran, SQL,

o Hands-on experience with tools like ANSYS Fluent, MATLAB/Simulink, and

Dymola.

o Familiarity with machine learning, signal processing, and optimization

techniques.

o Experience in model-based systems engineering (MBSE) methodologies.

o Knowledge of basic refrigerant cycles (e.g., single-stage compression cycle).

o Experience with embedded systems and lab testing.