Propulsion Engineer - AI Model Training – Remote

Job Type: Contractor

Location: Remote

Role Description

If you’re a senior propulsion engineer who thrives on technical precision, systems thinking, and rigorous engineering judgment, this is a unique opportunity to contribute directly to how the next generation of AI systems reason about aerospace and propulsion topics. We’re looking for propulsion specialists who have deep experience with propulsion architecture, combustion systems, thermal management, performance analysis, test campaigns, failure modes, and design tradeoffs. You’ll challenge and evaluate advanced language models on propulsion engineering topics to strengthen model reasoning, accuracy, and technical communication.

Your Profile

• 5 years of professional experience in propulsion engineering, aerospace engineering, rocket propulsion, spacecraft propulsion, launch vehicle systems, aircraft propulsion, or a closely related technical field.
• Significant hands-on work with propulsion system design, analysis, integration, test, qualification, anomaly resolution, or flight-support engineering.
• Deep knowledge of propulsion fundamentals, including thermodynamics, fluid mechanics, combustion, heat transfer, nozzle flow, pressurization, and system-level tradeoffs.
• Strong understanding of liquid, solid, hybrid, electric, or air-breathing propulsion systems, including performance metrics, operating constraints, and common failure modes.
• Bachelor’s degree in Aerospace Engineering, Mechanical Engineering, Propulsion Engineering, or a related field; advanced degree preferred for highly specialized propulsion domains.
• Previous experience with AI data training, annotation, or evaluating AI-generated technical content is a strong plus.
  
  

Key Responsibilities

• Evaluate AI-generated answers for technical accuracy, completeness, and reasoning quality across propulsion engineering topics.
• Challenge advanced language models with realistic propulsion scenarios, design tradeoffs, calculations, and edge cases.
• Review and refine AI-generated prompts, model responses, reasoning chains, and technical explanations.
• Identify subtle technical errors in areas such as thrust performance, chamber pressure, mixture ratio, cooling strategy, combustion behavior, test interpretation, and system integration.
• Provide structured feedback that helps improve model accuracy, reliability, and domain-specific reasoning.
• Shape AI communication standards for propulsion engineering by clarifying what high-quality technical explanations should include.