Aerospace Engineer - AI Model Training – Remote

Job Type: Contractor

Location: Remote

Role Description

If you’re an aerospace engineering expert who thrives on technical precision, systems thinking, and rigorous analysis, this is a unique opportunity to contribute directly to how the next generation of AI systems reason about flight, propulsion, structures, aerodynamics, controls, and mission-critical engineering decisions.We’re looking for senior Aerospace Engineer professionals with deep experience to strengthen model reasoning and technical accuracy.

Your Profile

• 4 years of professional experience as an Aerospace Engineer or in a closely related aerospace, aeronautical, astronautical, propulsion, structures, systems, or flight sciences role.
• Significant hands-on work with aerospace design, analysis, testing, simulation, verification, certification, or mission-critical engineering decision-making.
• Deep knowledge of aerospace fundamentals such as aerodynamics, propulsion, flight mechanics, orbital mechanics, structures, materials, controls, or systems engineering.
• Strong understanding of engineering tradeoffs, safety margins, model validation, boundary conditions, performance constraints, and technical risk assessment.
• Proven experience interpreting technical requirements, engineering drawings, simulation outputs, test data, or performance models.
• Demonstrated experience in explaining complex aerospace concepts clearly to technical stakeholders through written analysis, reviews, reports, or design documentation.
• Bachelor’s degree in Aerospace Engineering, Aeronautical Engineering, Mechanical Engineering, Astronautical Engineering, or a related field required; master’s degree or PhD preferred for highly specialized projects.
• Previous experience with AI data training, annotation, or evaluating AI-generated technical content is a strong plus.
  
  

Key Responsibilities

• Evaluate AI-generated aerospace engineering content for technical accuracy, completeness, assumptions, and reasoning quality.
• Challenge advanced language models with domain-specific prompts involving aerodynamics, propulsion, aircraft or spacecraft systems, structural mechanics, flight dynamics, controls, and test engineering.
• Review and refine AI-generated prompts, responses, calculations, explanations, and technical recommendations.
• Provide structured feedback that identifies errors, missing constraints, unsafe assumptions, weak reasoning, or unclear communication.
• Shape AI communication standards for aerospace topics by helping models respond with precision, appropriate caveats, and engineering judgment.
• Support benchmarking efforts by creating, reviewing, and scoring aerospace engineering tasks across varying levels of complexity.
• Assess whether AI outputs properly apply first principles, engineering standards, units, tolerances, boundary conditions, and safety factors.
• Compare multiple AI-generated answers and rank them based on technical correctness, clarity, and usefulness to professional users.