- Rémunération
- Non précisé
- Niveau
- Intermédiaire
- Mode
- À distance
- Lieu
- Worldwide
Le poste
Role Title: MBSE Engineer - SysML v2 Role Type: Contractor Location: Remote micro1 is engaging MBSE Engineer - SysML v2 experts to contribute to a customer's project focused on AI training and evaluation. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. Scope of Work
- Interpret and translate engineering requirements into accurate SysML v2 textual models, emphasizing model fidelity and traceability.
- Develop reference solutions and exemplar architectures in SysML v2 to serve as benchmarks for AI evaluation tasks.
- Create, refine, and document evaluation rubrics to assess the quality and correctness of SysML v2 models generated by AI systems.
- Review, assess, and provide structured feedback on SysML v2 models, ensuring technical accuracy and adherence to modeling best practices.
- Analyze requirements, ConOps, interface control documents (ICDs), and architectural specifications to inform modeling efforts.
- Collaborate asynchronously via written and verbal communication to clarify project deliverables and resolve technical ambiguities.
Preferred Qualifications
- Minimum 3 years of professional experience in systems engineering with demonstrated hands-on expertise in SysML v2 textual modeling.
- In-depth understanding of requirements engineering, system architecture, interface control, and model traceability.
- Experience working with ConOps, ICDs, and other foundational systems engineering artifacts.
- Proficient in technical writing and clear verbal communication, especially in remote or asynchronous project settings.
- Background in complex industries such as aerospace, space, defense, automotive, maritime, or communications is beneficial but not required.
- Familiarity with model assessment, rubric creation, or model review in a systems engineering context is a plus.
- Previous exposure to AI, ML, or data-driven engineering projects is advantageous
Originally posted on Himalayas