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MBSE Engineer (SysML v2)

70 - 120$
Формат работы
remote (Global)
Тип работы
fulltime
Грейд
senior
Английский
b2
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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TL;DR
MBSE Engineer (SysML v2) (AI systems): Developing textual system models, reference architectures, and evaluation rubrics for AI training and evaluation with an accent on requirements traceability, system architecture, and technical model fidelity. Focus on interpreting ConOps and ICDs, reviewing AI-generated SysML v2 models, and providing structured feedback on modeling accuracy and compliance.

Location: Remote

Salary: $70–$120 per hour

Company

hirify.global delivers engineering and AI training and evaluation projects.

What you will do

  • Translate engineering requirements into accurate SysML v2 textual models with fidelity and traceability.
  • Develop reference solutions and exemplary system architectures for AI evaluation benchmarks.
  • Create and refine evaluation rubrics for assessing AI-generated SysML v2 models.
  • Review models and provide structured technical feedback on accuracy and modeling best practices.
  • Analyze ConOps, ICDs, requirements, and architectural specifications to support modeling.
  • Communicate in writing and verbally to clarify deliverables and resolve technical ambiguities.

Requirements

  • Professional systems engineering experience with hands-on SysML v2 textual modeling expertise.
  • In-depth knowledge of requirements engineering, system architecture, interface control, and model traceability.
  • Experience with ConOps, ICDs, and other foundational systems engineering documents.
  • Strong technical writing and verbal communication skills, including in remote and asynchronous environments.
  • Ability to evaluate system models and provide clear, structured technical feedback.

Nice to have

  • Experience in aerospace, space, defense, automotive, maritime, communications, or other complex industries.
  • Familiarity with model assessment, evaluation rubric development, or systems engineering model review.
  • Exposure to AI, machine learning, or data-driven engineering projects.

Culture & Benefits

  • Remote contractor engagement.
  • Work supporting next-generation AI training and evaluation systems.

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