Remote | Aerodynamics Expert (MSc. or PhD) — $80–$120/hour

24-Mag • New York, NY

7d • Remote

About The Position

24-MAG LLC is recruiting experienced aerodynamics and computational fluid dynamics professionals for a fully remote freelance consulting engagement supporting advanced AI training and evaluation. The work combines applied aerodynamics, fluid mechanics, CFD simulation, Python programming, numerical modelling, scientific computing, and technical review. Consultants will develop, solve, review, and validate engineering problems involving aerodynamic systems, computational meshes, and fluid-flow analysis to help improve advanced AI systems’ accuracy, reasoning, and computational capabilities.

The work includes defining aerodynamic problems and computational models; preparing geometries, meshes, simulation conditions, and solver configurations; running and evaluating CFD analyses; and building Python-based workflows for simulation automation and postprocessing. Consultants will also create reproducible reference solutions, assess AI-generated engineering work, diagnose numerical and modelling issues, and document assumptions, methods, validation results, and conclusions. Compensation is advertised at $80–$120 per hour, with output-based payment per completed task that meets project specifications. Expected commitment is approximately 15 hours per week, with flexible working hours and days, including weekends. The opportunity is open worldwide and lists 100 openings. Selection may include screening questions, an approximately 30-minute AI interview, and a hiring manager review. Selected professionals should be prepared to begin their first assignment within 24–48 hours after onboarding. Work must not use confidential or proprietary third-party information.

Requirements

• Master's degree (MSc/MS) or PhD in Aerospace Engineering, or Mechanical Engineering with a specialisation in aerodynamics, fluid dynamics, or thermofluids; alternatively, a bachelor's degree in Aerospace or Mechanical Engineering with at least 1–2 years of aerodynamics-specific professional or research experience.
• Strong understanding of fluid mechanics, applied aerodynamics, computational methods, and engineering simulation principles.
• Demonstrated experience formulating, executing, and evaluating CFD or aerodynamic analyses.
• Practical proficiency with Python for scientific computing, numerical analysis, or engineering automation.
• Experience using at least one engineering tool accessible through a command-line interface, scripting environment, configuration files, or programmatic API.
• Ability to develop computational geometries, meshes, solver-ready cases, and reproducible simulation workflows.
• Ability to define and justify modelling assumptions, fluid properties, boundary conditions, mesh strategies, and numerical solver settings.
• Strong understanding of aerodynamic quantities, including lift, drag, pressure distributions, and relevant flow characteristics.
• Ability to diagnose non-convergent simulations, numerical instability, incorrect results, and physically invalid outputs.
• Experience automating simulation execution, parameter studies, postprocessing, or engineering validation procedures.
• Strong analytical reasoning, mathematical problem-solving, critical thinking, and technical research capabilities.
• Ability to evaluate computational results and explain engineering assumptions, numerical limitations, and technical trade-offs.
• Exceptional attention to detail and commitment to accurate, reproducible, well-documented engineering work.
• Excellent written communication skills, including the ability to explain sophisticated aerodynamic concepts and computational findings clearly.
• Ability to work independently and manage complex technical assignments in a remote environment.
• Practical experience with programmatically accessible engineering tools and computational simulation workflows.

Nice To Haves

• Familiarity with engineering software such as OpenFOAM, SU2, Gmsh, FEniCSx, Elmer, CalculiX, or comparable computational tools.
• Familiarity with Python libraries such as NumPy, SciPy, pandas, Matplotlib, Jupyter, or relevant domain-specific scientific packages.
• Prior experience with AI training, model evaluation, or related technology initiatives.

Responsibilities

• Develop technically rigorous engineering problems involving applied aerodynamics, fluid mechanics, and computational fluid dynamics.
• Analyse aerodynamic systems, airfoil configurations, flow conditions, and physical constraints.
• Translate engineering requirements into computational models and simulation-based tasks.
• Apply fluid-dynamics principles to evaluate lift, drag, pressure distributions, and aerodynamic performance.
• Contribute engineering expertise to AI training and evaluation problems.
• Design and evaluate CFD models for aerodynamic flows and complex fluid-dynamics scenarios.
• Create or modify engineering geometries, computational domains, and numerical meshes.
• Define fluid properties, initial and boundary conditions, and solver configurations.
• Execute aerodynamic simulations using command-line-accessible engineering tools and computational solvers.
• Assess modelling assumptions, mesh strategies, and numerical methods for engineering applications.
• Develop Python workflows for aerodynamic analysis, scientific computing, and engineering simulation.
• Automate preprocessing, mesh preparation, simulation execution, parameter sweeps, and postprocessing.
• Use scientific computing libraries to analyse aerodynamic datasets and simulation outputs.
• Create reproducible computational workflows using programmatic engineering tools and solver interfaces.
• Evaluate code implementations for technical correctness, efficiency, reproducibility, and alignment with requirements.
• Create realistic aerodynamic and fluid-dynamics problems requiring advanced engineering reasoning and numerical analysis.
• Develop accurate reference solutions using reproducible computations and documented methodologies.
• Review and validate AI-generated engineering analyses, Python implementations, CFD configurations, and technical explanations.
• Identify errors in modelling assumptions, boundary conditions, numerical calculations, and simulation procedures.
• Provide technical feedback to improve AI performance on CFD and aerodynamic problem-solving tasks.
• Evaluate CFD results for numerical convergence, physical validity, and consistency with engineering principles.
• Diagnose simulation instability, non-convergence, incorrect solver configurations, and physically implausible results.
• Assess mesh quality, discretisation choices, solver settings, and the reliability of calculated aerodynamic quantities.
• Document analytical methods, computational assumptions, validation results, and engineering conclusions.
• Apply rigorous quality standards to simulation workflows, numerical analysis, and AI evaluation deliverables.

What This Job Offers

• Career Level: Mid Level