MBSE Engineer - SysML v2

Pay: $55 - $120/hour

Required Skills
sysml v2
systems engineering
requirements engineering
system architecture
model traceability
interface control documents (icds)
conops
technical writing
model assessment
rubric creation
model review
asynchronous communication
remote collaboration
ai/ML familiarity
aerospace/defense/automotive industry background
About micro1
micro1 is a data lab that helps AI labs & Enterprises train foundational models and agents. We provide frontier evaluations and reinforcement learning environments to improve LLM capabilities, as well as contextual evaluations to monitor and improve AI agents in enterprise settings.

Our AI recruiting agent sources and vets domain experts for our data platform that enables rapid production of high-quality training data. Our research spans high-value, specialized domains (legal, medical, finance, coding, etc.), where expert-level data is the hardest to produce and most valuable for advanced model performance. Our pipeline performance system ensures both quality and velocity.

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 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.
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