Aerodynamics Expert for CFD AI Training

About OpenTrain AI

OpenTrain AI is the hiring and contracting organization for this role. OpenTrain helps people build careers in AI training and data labeling, where skilled contributors prepare, evaluate, and improve the examples used to develop modern AI systems.

• Fully remote work with flexible scheduling
• Contractor opportunity for under 20 hours per week
• Compensation of $80–$130 per hour
• Work available to candidates in the United Kingdom, United States, Canada, India, Germany, and Switzerland

About AI Training and Engineering Evaluation

AI training is the human side of building artificial intelligence. Experts create, review, and rate high-quality examples so AI systems can produce more accurate and technically sound results. In this project, your engineering judgment will help assess AI-generated computational fluid dynamics and aerodynamics work.

• Apply specialist knowledge to cutting-edge AI development
• Review technical reasoning, assumptions, configurations, and outputs
• Create reproducible reference solutions and validation criteria

The Aerodynamics Expert Role

OpenTrain AI is seeking an intermediate-level Aerodynamics Expert with strong computational fluid dynamics knowledge and practical Python experience. You will create, solve, review, and validate engineering tasks completed through programmatic, command-line-based workflows.

A representative task may involve analyzing an airfoil, preparing a computational domain and mesh, defining boundary conditions, running a CFD simulation, calculating lift and drag, and determining whether the flow field is numerically and physically valid. Solutions must be reproducible through code, scripts, configuration files, or command-line tools; experience limited exclusively to graphical user interfaces is not sufficient.

• Contractor, part-time engagement
• Expected commitment: under 20 hours per week
• Expected project duration: 1 to 3 months
• Flexible hours and days, including weekends if desired
• Candidates should be ready to begin immediately
• Roles are typically filled within 48 hours

What You’ll Work On

You will solve and validate aerodynamic and fluid-dynamics problems while translating physical requirements into computational models and solver-ready cases. The work combines engineering analysis, programmatic simulation, technical review, and clear documentation of reasoning and trade-offs.

• Create or modify geometries, computational domains, and meshes
• Define initial conditions, boundary conditions, fluid properties, and solver settings
• Run CFD and aerodynamic-analysis workflows with 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
• Perform 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

Required Qualifications

You should have strong fluid mechanics and applied aerodynamics knowledge, along with experience formulating and executing CFD or aerodynamic analyses. You must be able to select and justify modeling assumptions, mesh strategies, boundary conditions, and solver settings.

An MS or PhD in Aerospace Engineering, or Mechanical Engineering with an aerodynamics, fluid dynamics, or thermofluids specialization, is acceptable. A BS in Aerospace or Mechanical Engineering plus at least 1–2 years of aero-specific professional or research experience is also accepted.

• Practical proficiency with Python
• Experience using at least one engineering tool or library through a CLI, scripting interface, configuration files, or programmatic API
• Ability to diagnose non-convergence, unstable solutions, incorrect results, and physically invalid outputs
• Ability to communicate technical reasoning and engineering trade-offs clearly
• Fluent English proficiency
• Candidates must be based in the United Kingdom, United States, Canada, India, Germany, or Switzerland

Relevant Tools and Technical Experience

Experience with any equivalent programmatic engineering software is acceptable. No single tool or Python library is mandatory, provided you can complete reproducible command-line or scripted workflows.

• Relevant engineering tools may include OpenFOAM, SU2, Gmsh, FEniCSx, Elmer, CalculiX, SciPy, or similar software
• Relevant Python tools may include NumPy, SciPy, pandas, Matplotlib, Jupyter, solver APIs, mesh-processing libraries, or domain-specific scientific packages
• Experience should support scripting, configuration, automation, analysis, or programmatic solver access

Compensation and Availability

Compensation is output-based. Experts are paid per task that meets project specifications, and the time required for each task may vary based on experience and workflow. Minimum submission requirements apply.

This is a flexible, fully remote contractor opportunity requiring less than 20 hours per week. The project is expected to run for 1 to 3 months.

• $80–$130 per hour
• Under 20 hours per week
• Flexible schedule, with weekends optional
• Immediate-start availability preferred

Application and Screening Process

To apply, submit your application through OpenTrain AI and complete the required evaluation steps. The technical screening is designed to assess your own aerodynamics, CFD, and engineering judgment.

• Apply to the role and complete the screening questions
• Complete an approximately 30-minute AI interview
• Complete a technical assessment if required
• Complete the hiring manager review
• Create and use a new email address when applying online
• Do not use AI tools during the technical screening assessment; AI assistance will lead to immediate rejection