CFD Simulation Engineer

Critical Fit Recruiting; Phoenix (AZ); Sur place; USD 110 000 - 150 000; Plein temps

Résumé du poste

Critical Fit Recruiting, on behalf of a leading engineering organization in Phoenix, seeks an Engineer to integrate CFD, thermal design, CAD, and experimental validation to tackle high‑power‑density cooling challenges.

You will own simulation methods, automate setup and reporting with Python, develop DoEs and surrogate models, and translate customer constraints into scalable cooling architectures for manufacturable solutions.

Qualifications

• 3+ years of industrial simulation or product-development experience.
• Strong ANSYS Fluent capability with conjugate heat transfer, internal flow, and pressure-drop prediction.
• Experience with CAD, DoE, optimization, surrogate models, Python automation, and simulation-to-test correlation.
• Ability to distinguish numerical convergence from physical credibility and translate results into manufacturable design recommendations.
• Experience with HPC, electronics cooling, or high-power-density systems is highly desirable.

Responsabilités

• Perform CFD, conjugate heat-transfer, thermal, and Multiphysics analyses for liquid-cooled electronics, with strong emphasis on ANSYS Fluent.
• Develop models for conduction, convection, pressure loss, flow maldistribution, manifolds, interfaces, material behavior, cold plates, microchannels, heat spreaders, and vapor chambers.
• Identify limits in meshing, convergence, model size, solver performance, compute capacity, and simulation time; recommend model reduction, surrogate methods, automation, or additional computing resources.
• Use Python and AI-assisted coding to automate setup, execution, post-processing, optimization, visualization, and reporting. Validate all generated code and models through physics checks, conservation, mesh independence, benchmarks, cross-tool comparison, and test correlation.
• Build simulation DoEs, response surfaces, and Pareto diagrams to balance temperature, thermal resistance, pressure drop, flow uniformity, package limits, manufacturability, robustness, cost, and reliability.
• Convert simulation trade spaces into targeted experimental plans; correlate results, quantify uncertainty, investigate discrepancies, and improve reusable validation methods.
• Translate customer power maps, coolant conditions, allowable temperatures, pressure-drop limits, and package constraints into practical cooling architectures.

Connaissances

ANSYS Fluent

Conjugate heat transfer

Python automation

DoE design of experiments

Optimization

CAD

Formation

Bachelor/Master/PhD in Mechanical/Aerospace/Physics/Applied Math

Outils

ANSYS Fluent

Python scripting

CAD tools (SolidWorks/CATIA)

Description du poste

DESCRIPTION:

The Engineer will connect CFD, thermal design, CAD, optimization, manufacturing, and experimental validation to convert high-power-density cooling challenges into scalable products. The position offers growth beyond conventional CFD analysis through ownership of simulation methods, automation, design rules, and customer-facing technical recommendations.

RESPONSIBILITIES:

• Perform CFD, conjugate heat-transfer, thermal, and Multiphysics analyses for liquid-cooled electronics, with strong emphasis on ANSYS Fluent.
• Develop models for conduction, convection, pressure loss, flow maldistribution, manifolds, interfaces, material behavior, cold plates, microchannels, heat spreaders, and vapor chambers.
• Identify limits in meshing, convergence, model size, solver performance, compute capacity, and simulation time; recommend model reduction, surrogate methods, automation, or additional computing resources.
• Use Python and AI-assisted coding to automate setup, execution, post-processing, optimization, visualization, and reporting. Validate all generated code and models through physics checks, conservation, mesh independence, benchmarks, cross-tool comparison, and test correlation.
• Build simulation DoEs, response surfaces, and Pareto diagrams to balance temperature, thermal resistance, pressure drop, flow uniformity, package limits, manufacturability, robustness, cost, and reliability.
• Convert simulation trade spaces into targeted experimental plans; correlate results, quantify uncertainty, investigate discrepancies, and improve reusable validation methods.
• Translate customer power maps, coolant conditions, allowable temperatures, pressure-drop limits, and package constraints into practical cooling architectures.

Qualifications:

• Bachelor's, Master's, or PhD in Mechanical Engineering, Aerospace Engineering, Physics, Applied Mathematics, Materials Science, or a related discipline.
• 3+ years of industrial simulation or product-development experience.
• Strong ANSYS Fluent capability and practical experience with conjugate heat transfer, internal flow, pressure-drop prediction, meshing, convergence, and model verification.
• Experience with CAD, DoE, optimization, surrogate models, Python automation, and simulation-to-test correlation.
• Ability to distinguish numerical convergence from physical credibility and translate results into manufacturable design recommendations.
• Experience with HPC, AI accelerators, electronics packaging, liquid cooling, or high-power-density systems is highly desirable.