WFH.teamOpen app$114k-$250k
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Decision details from the source listing
flexible
Approximately 15 hours per week; variable hours depending on project needs
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What this posting tells you
Remote contractor opportunity supporting an AI training and evaluation project. The work involves creating SysML v2 reference models, evaluating AI-generated models, and developing quality rubrics. Hours are variable and flexible at approximately 15 hours per week; the pilot is expected to last 4 weeks to 3 months. Compensation amount is not stated.
Data, Operations, Product, Software, Customer support, Writing and content
Eligible countries are not stated.
Timezone overlap is not stated.
Experienced professional; level not specified · Contractor
- Eligible hiring countries are not stated
- Required timezone overlap is not stated
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This role's listed pay is above the median among 200 comparable roles shown here. Category counts come from WFH.team's latest published remote job market snapshot.
Explore the remote job marketMBSE Engineer - SysML V2 at micro1
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.
Working remotely at micro1
micro1 builds human-expertise data and evaluation infrastructure for AI models and agents. It recruits core-team employees and domain experts for AI training projects.
- Headquarters
- San Francisco Bay Area, California, United States
- Founded
- 2022
Expert opportunities are remote and can be flexible. International applicants are considered, subject to country exclusions and each project's requirements. Core-team work arrangements vary by opening; check the individual posting.
Apply through the official posting. Expert applicants complete an AI interview and skills certification, followed by project selection and onboarding. Certification does not guarantee a project or immediate work.