micro1 / Software
MBSE Engineer - SysML v2
nuevaDesde Argentina
- Remoto desde Argentina
- Contrato
- USD 55 – 120/h
- Remoto
- Semi senior
- 3+ años de experiencia
Requisitos
- • 3+ años de experiencia
- • inglés intermedio o más (el aviso está escrito en inglés)
Suma si tenés
- machine learning
- inteligencia artificial
La búsqueda
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
Publicado en Himalayas. Los datos de requisitos los extrae Maru del aviso: ante cualquier duda, manda el aviso original.