Aerodynamics Engineer for AI Training

Role Overview

Apply aerodynamics and computational fluid dynamics expertise to create, solve, review, and validate engineering tasks for AI training. This work centers on reproducible, programmatic and command-line workflows, including aerodynamic analysis, engineering simulation, and Python automation.

A representative assignment may involve analyzing an airfoil, preparing a computational domain and mesh, setting boundary conditions, running a CFD simulation, calculating lift and drag, and determining whether the flow field is numerically and physically valid.

Key Responsibilities

• Solve and validate aerodynamics and fluid-dynamics problems.
• Convert physical requirements into computational models and solver-ready cases.
• Create or modify geometries, computational domains, and meshes.
• Define initial conditions, boundary conditions, fluid properties, and solver settings.
• Run CFD and aerodynamic-analysis workflows through command-line-accessible tools.
• Use Python for preprocessing, simulation execution, parameter sweeps, postprocessing, and validation.
• Analyze pressure, velocity, forces, moments, lift, drag, pressure loss, and other relevant outputs.
• Diagnose mesh-quality, convergence, numerical-stability, turbulence-modeling, and boundary-condition issues.
• Conduct mesh-independence studies, sanity checks, and comparisons with analytical, experimental, or reference results.
• Review AI-generated engineering solutions for incorrect assumptions, invalid configurations, and physically unrealistic outputs.
• Develop clear, reproducible reference solutions and verification criteria.

Qualifications

• MS or PhD in Aerospace Engineering, or Mechanical Engineering with an aerodynamics, fluid dynamics, or thermofluids specialization, or a BS in Aerospace or Mechanical Engineering plus 1 to 2 years of aerodynamics-specific professional or research experience.
• Strong knowledge of fluid mechanics and applied aerodynamics.
• Experience formulating and performing CFD or aerodynamic analyses.
• Practical Python proficiency.
• Experience with at least one engineering tool or library operable through a CLI, scripting interface, configuration files, or programmatic API.
• Ability to select and justify modeling assumptions, boundary conditions, mesh strategies, and solver settings.
• Ability to diagnose non-convergence, unstable solutions, incorrect results, and physically invalid outputs.
• Ability to clearly communicate technical reasoning and engineering trade-offs.
• Relevant tools may include OpenFOAM, SU2, Gmsh, FEniCSx, Elmer, CalculiX, SciPy, or similar programmatic tools.
• Experience exclusively with graphical interfaces is insufficient, because solutions must be reproducible through code, scripts, configuration files, or command-line tools.

Work Terms

• Independent contractor engagement.
• Fully remote, open globally.
• Approximately 15 hours per week.
• Flexible schedule, with choice of working hours and days, including weekends if desired.

Compensation

$80 to $130 per hour.