- Anywhere in the World
MBSE Engineer - SysML V2
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Deskripsi pekerjaan
2 menit bacaRole type: Contractor
Location: Remote
Commitment: Pay-per- task-based, variable/flexible hours (~15hrs/wk)
Project duration: ~ 4 weeks to 3 months
About the opportunity
micro1 is looking for experienced Model-Based Systems Engineering (MBSE) professionals with expertise in SysML v1 and exposure to SysML v2, or demonstrated hands-on experience with SysML v2 modeling, to support a customer project focused on AI training and evaluation.
In this role, you'll apply your systems engineering knowledge to develop reference models, assess AI-generated SysML v2 outputs, and establish clear standards for technical accuracy and model quality.
Candidates may use suitable SysML modeling tools to create and evaluate system models. Experience with graphical or textual modeling approaches is welcome.
Your expertise will help evaluate how effectively AI systems interpret engineering requirements, represent complex system architectures, and produce consistent, traceable models.
What you’ll do
- Interpret and translate engineering requirements into accurate SysML v2 models, emphasizing model fidelity and traceability
- Develop reference solutions and exemplar system architectures using SysML v2 to serve as benchmarks for AI evaluation tasks
- Use appropriate systems modeling tools to create, review, and validate SysML v2 models
- Create, refine, and document evaluation rubrics to assess the quality and correctness of AI-generated SysML v2 models
- Review, assess, and provide structured feedback on SysML v2 models, ensuring technical accuracy and adherence to modeling best practices
- Analyze requirements, Concepts of Operations (ConOps), Interface Control Documents (ICDs), and architectural specifications to inform modeling efforts
- Collaborate asynchronously through written and verbal communication to clarify project deliverables and resolve technical ambiguities
Required qualifications
- Professional experience in systems engineering, with hands-on expertise in SysML v1 and some exposure to SysML v2, or demonstrated experience with SysML v2 modeling
- Ability to interpret engineering requirements and translate them into technically accurate system models
- Understanding of model-based systems engineering principles, requirements traceability, and system architecture
- Experience working with systems modeling tools and applying MBSE methodologies to engineering projects
Preferred qualifications
- Strong understanding of requirements engineering, system architecture, interface control, and model traceability
- Experience using MBSE modeling tools such as Cameo Systems Modeler, MagicDraw, or other compatible systems modeling applications
- Familiarity with SysML v2 modeling environments, including graphical or textual approaches
- Experience working with ConOps, ICDs, and other foundational systems engineering documentation
- Strong technical writing and communication skills, particularly in remote or asynchronous environments
- Experience in complex engineering domains such as aerospace, space, defense, automotive, maritime, or communications
- Familiarity with model verification, technical review, evaluation rubric development, or model quality assessment
- Exposure to AI, machine learning, or data-driven engineering projects
Engagement details
Contract type: Contractor engagement.
Location: Remote.
Work structure: Project or task-based, with variable hours depending on project needs.
Duration: Initial pilot expected to last approximately 4 weeks to 3 months.
Application process
- Candidates will complete an AI interview as part of the application process
Originally posted on Himalayas
Hitung gaji bersih dalam rupiah
Perkiraan kasar: kurs USD Rp17.800; pajak dihitung sebagai penghasilan orang pribadi (tarif progresif PPh 21, dikurangi PTKP), tanpa NPPN, iuran BPJS, atau potongan lain. Bukan nasihat pajak; cek ketentuan terbaru atau konsultan pajak.
Tips melamar
- Sebutkan lokasi dan zona waktumu di bagian atas CV, mis. Jakarta, Indonesia (GMT+7).
- Sesuaikan ringkasan CV dengan kata kunci di deskripsi, terutama Machine Learning.
- Tulis hasil kerja dengan angka (mis. "menangani 60 tiket/hari"), bukan hanya tugas.
- Perusahaan resmi tidak pernah meminta biaya untuk melamar atau wawancara.
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