MBSE Engineer SysML v2 AI Model Evaluation

You will support AI training and evaluation by turning engineering requirements into accurate, traceable SysML v2 textual models. You will also review AI-generated systems engineering content and explain technical issues in clear written and verbal feedback.

The work uses systems engineering documents and requires careful judgment about requirements, architectures, interfaces, and model quality.

• Create high-fidelity SysML v2 textual models from engineering requirements.
• Develop reference solutions and exemplar architectures for AI evaluation tasks.
• Create and refine rubrics for judging AI-generated SysML v2 models.
• Review model outputs for technical issues and provide structured feedback.
• Use Concepts of Operations, interface control documents, and architectural specifications to guide modeling decisions.
• Communicate asynchronously in writing and verbally to clarify deliverables and resolve technical ambiguities.

What it pays and takes

This is a remote, part-time contractor role with asynchronous collaboration. Weekly hours and project duration are to be confirmed.

• Pay: $55 to $120 per hour.
• Location: Remote; open to candidates in these country codes: AE, AR, AT, BD, BE, BH, BR, CA, CH, CL, CO, DE, DK, DZ, EG, ES, FR, GB, GH, GR, ID, IN, IT, JO, JP, KE, KG, KW, KZ, LB, LK, MA, MX, MY, NG, NL, OM, PE, PH, PK, PS, PT, QA, SA, SG, TH, TN, TW, US, UZ, VN, ZA.
• Language: Professional fluency in English.
• Required expertise: Hands-on experience writing SysML v2 models with textual notation, plus strong knowledge of requirements engineering, system architecture, interface control, and model traceability.
• Required systems engineering background: Direct experience with ConOps, ICDs, and other systems engineering artifacts.
• Communication: Strong technical writing and verbal communication skills for remote, asynchronous collaboration.
• Helpful background: Aerospace, space systems, defense, automotive, maritime, communications, model assessment, rubric creation, model review, or AI, machine learning, and 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 uses human judgment to prepare examples, review model responses, and evaluate whether AI-generated content is accurate and useful. People with specialized systems engineering knowledge are needed for tasks that require careful technical review.