Aerospace Engineer - AI Model Training – Remote

YO IT Consulting; Toronto; On-site; CAD 90,000 - 120,000; Part time

Job summary

YO IT Consulting is looking for a senior Aerospace Engineer in Canada, Ontario, Toronto. The role involves evaluating AI-generated aerospace engineering content, ensuring technical accuracy, and refining AI responses related to aerospace topics.

The ideal candidate will have a Bachelor’s degree in Aerospace Engineering and over 4 years of experience in related roles. You will work remotely, contributing to advanced projects that push the boundaries of AI in aerospace.

Qualifications

• 4+ years of experience in Aerospace Engineering or related fields.
• Hands-on work with aerospace design, analysis, and testing.
• Deep knowledge of fundamentals like aerodynamics and propulsion.

Responsibilities

• Evaluate AI-generated aerospace engineering content for accuracy.
• Challenge AI models with domain-specific prompts.
• Review and refine AI-generated technical recommendations.

Skills

Aerospace Engineering expertise

Technical precision

Systems thinking

Analytical skills

Education

Bachelor’s degree in Aerospace Engineering

Master’s degree or PhD preferred

Tools

Simulation software

Engineering analysis tools

Job description

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.