Senior MBSE Engineer - SysML v2

Micro1; India; Remote; INR 1,653,000 - 3,444,000; Part time

Job summary

Cashback24x7 is seeking an experienced MBSE Engineer to support AI training and evaluation tasks. You will translate requirements into SysML v2 textual models, build reference architectures, and develop evaluation rubrics to assess model quality.

This remote contractor role offers about 15 hours per week, with a pilot/engagement lasting roughly 4 weeks to 3 months. Strong SysML v1 background with exposure to SysML v2 and MBSE practices are essential.

Qualifications

• Professional experience in systems engineering with hands-on SysML v1 and exposure to SysML v2.
• Ability to translate requirements into technically accurate system models.
• Understanding MBSE principles, traceability, and architecture.

Responsibilities

• Translate engineering requirements into SysML v2 textual models with fidelity and traceability.
• Develop reference SysML v2 models and exemplar architectures for AI evaluation.
• Create and document evaluation rubrics to assess SysML v2 models generated by AI.
• Review and provide structured feedback on SysML v2 models for accuracy and best practices.
• Analyze ConOps, ICDs, and architectural specs to guide modeling efforts.
• Collaborate asynchronously to clarify deliverables.

Skills

SysML v2

SysML v1

MBSE

Requirements traceability

System architecture

Technical writing

Job description

MBSE Engineer - SysML v2

Role Details

• Role 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 hands-on experience with SysML v2 textual 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. Your expertise will help evaluate how effectively AI systems interpret engineering requirements, represent complex system architectures, and produce consistent, traceable models.

Key Responsibilities

• 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, 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 textual 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.

Preferred Qualifications

• Strong understanding of requirements engineering, system architecture, interface control, and model traceability.
• 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.