Aerodynamics Engineer -AI Model Training – Remote

Job Type: Contractor

Location: Remote

Role Description

If you’re a senior aerodynamics engineer who thrives on precision and complex technical evaluation, this is a unique opportunity to contribute directly to how advanced AI systems understand the field. We’re looking for experienced specialists who can evaluate nuanced engineering concepts. You’ll challenge and evaluate advanced language models on aerodynamics-specific topics to strengthen model reasoning, accuracy, and technical communication.

Your Profile

• 5 years of professional experience as an Aerodynamics Engineer, Aerospace Engineer, CFD Engineer, or closely related technical specialist.
• Significant hands-on work with aerodynamic analysis, CFD simulation, wind tunnel testing, flight vehicle performance assessment, airfoil/wing design, or aerodynamic optimization.
• Deep knowledge of fluid mechanics, external aerodynamics, boundary layer theory, turbulence, lift and drag generation, compressible flow, and aerodynamic scaling principles.
• Strong understanding of CFD methodologies, meshing considerations, turbulence models, numerical convergence, validation practices, and limitations of simulation-based analysis.
• Proven experience interpreting aerodynamic data, identifying performance tradeoffs, and communicating technical findings to engineering, research, or product teams.
• Demonstrated experience in aerodynamic design reviews, technical documentation, test planning, model validation, or applied aerospace engineering problem solving.
• Bachelor’s degree in Aerospace Engineering, Mechanical Engineering, Aeronautical Engineering, or a closely related field required; master’s degree or PhD preferred.
• Previous experience with AI data training, annotation, or evaluating AI-generated technical content is a strong plus.
  
  

Key Responsibilities

• Evaluate AI-generated aerodynamics explanations, calculations, assumptions, and engineering recommendations for technical correctness, clarity, and rigor.
• Challenge advanced language models with domain-specific prompts involving fluid mechanics, aerodynamic design, CFD interpretation, wind tunnel data, aircraft performance, and related aerospace engineering topics.
• Review and refine AI-generated prompts, model responses, worked examples, and technical explanations to ensure they reflect sound engineering reasoning.
• Identify errors, omissions, hallucinations, and weak assumptions in AI outputs related to aerodynamic theory, simulation workflows, experimental methods, and aircraft design tradeoffs.
• Provide structured feedback that helps improve AI model behavior, including detailed notes on reasoning gaps, terminology misuse, incomplete analysis, and unsafe or misleading conclusions.
• Shape AI communication standards for technical aerospace content, ensuring responses are accurate, well-scoped, and appropriate for professional engineering contexts.
• Support benchmarking efforts by designing, reviewing, or validating aerodynamics tasks that test model performance on real-world engineering reasoning.
• Compare multiple AI-generated responses and rank them based on technical quality, completeness, correctness, and usefulness to engineering users.