Senior MBSE Engineer SysML v2

The work

You will support AI training and evaluation by turning engineering requirements into accurate, traceable SysML v2 textual models. You will also help define reliable ways to assess AI-generated systems engineering content.

The work combines systems engineering judgment, structured model review, technical writing, and feedback on modeling quality.

• Interpret requirements and produce high-fidelity SysML v2 models using textual notation.
• Create reference solutions and example architectures for AI evaluation tasks.
• Create and refine rubrics for judging the quality and correctness of AI-generated SysML v2 models.
• Review model outputs, identify technical issues, and provide structured feedback based on modeling best practices.
• Use Concepts of Operations, interface control documents, and architectural specifications to guide modeling decisions.
• Communicate in writing and verbally to clarify deliverables and resolve technical questions.

What it pays and takes

This is a remote contractor role with asynchronous collaboration.

• Pay: $55 to $120 per hour.
• Time: Less than 20 hours per week.
• Project duration: To be confirmed.
• Location: Remote and open to candidates in the countries listed below.
• Countries: United Arab Emirates, Argentina, Austria, Bangladesh, Belgium, Bahrain, Brazil, Canada, Switzerland, Chile, Colombia, Germany, Denmark, Algeria, Egypt, Spain, France, United Kingdom, Ghana, Greece, Indonesia, India, Italy, Jordan, Japan, Kenya, Kyrgyzstan, Kuwait, Kazakhstan.
• Countries: Lebanon, Sri Lanka, Morocco, Mexico, Malaysia, Nigeria, Netherlands, Oman, Peru, Philippines, Pakistan, Palestine, Portugal, Qatar, Saudi Arabia, Singapore, Thailand, Tunisia, Taiwan, Uzbekistan, Vietnam, South Africa, and the United States.
• Language: Fluent English.
• Experience: At least three years of professional systems engineering experience.
• Technical skills: Hands-on experience writing SysML v2 models with textual notation, plus knowledge of requirements engineering, system architecture, interface control, and model traceability.
• Systems engineering materials: Direct experience with Concepts of Operations, interface control documents, and other architectural or systems engineering specifications.
• Communication: Strong technical writing and verbal communication skills for remote, asynchronous collaboration.
• Helpful background: Aerospace, space systems, defense, automotive, maritime, or communications experience; model assessment, rubric creation, model review, AI, machine learning, or data-driven engineering projects.

How it works

You apply here in about two minutes and finish on the hiring platform. The next step is a short AI interview (technical roles include a coding challenge). Passing it is how you qualify for paid tasks, so take it soon after you are invited.

The hiring platform's application for this job asks for your resume, your LinkedIn profile, your phone number, your location and answers to 8 screening questions.

About AI training work

AI training work is the human side of building AI systems. People prepare examples, review model responses, and assess technical outputs so AI systems can produce more accurate and useful results.