Remote job · Engineering
Freelance Mechanical CFD Engineer, AI Trainer
In one line: Freelance Mechanical CFD Engineer, AI Trainer is a remote role in Japan at a global AI training platform.
- Remote (Japan)
- A global AI training platform
- Posted 6 Oct 2026
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https://keywordise.com/mcpApply to Keywordise job tsymjc64r3About the role
You will help train and assess AI agents on expert fluid simulation tasks, preparing reference solutions and automated checks for their results. The work is freelance and fully remote.
At a glance
- PayNot stated in the posting
- Remote scopeRemote, Japan
- Posted6 Oct 2026
- Last checked20 Oct 2026
What you will do
- Set up and run simulations from CAD geometry
- Produce verified reference solutions for simulation tasks
- Write Python checks that evaluate the agent's results
- Assess AI agent output on expert-level fluid simulation work
What they look for
- Several years of hands-on CFD experience in industry or research, including meshing
- Proficiency with OpenFOAM, ANSYS Fluent or CFX, or STAR-CCM+
- Solid verification and validation practice, including mesh-independence studies and benchmark or experimental validation
- Comfort with Python and GitHub
- English at B2 level or higher
Nice to have
- Background in aerospace, automotive, offshore or turbomachinery
- Experience with multiphase or particle-laden flows
Benefits
- Fully remote work on your own schedule with a laptop and stable internet
- Performance-based bonus programs rewarding high-quality, consistent delivery
Questions about this job
Can I do this job remotely, and from which countries?
Yes, it is listed as remote, aimed at candidates in Japan.
What does this job pay?
The posting does not state a salary, so there is no figure to quote.
What experience is needed?
The posting asks for: several years of hands-on CFD experience in industry or research, including meshing; proficiency with OpenFOAM, ANSYS Fluent or CFX, or STAR-CCM+; solid verification and validation practice, including mesh-independence studies and benchmark or experimental validation.
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