Computational Fluid Dynamics Engineer - AI Trainer

Benefits

Parental leave

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Non-birth-parent leave

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Mental health support

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Relocation assistance

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Learning budget

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Mid From the posting source checked Jun 20, 2026

Work mode

Remote From the posting source checked Jun 20, 2026

In-office days

0 days From the posting source checked Jun 20, 2026

Schedule

Shift type

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Weekend work

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Application

Cover letter

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Assessment

Not required From the posting source checked Jun 20, 2026

Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Computational Fluid Dynamics Engineer - AI Trainer Remote (USA), Remote, United States Opportunity Overview Handshake is looking for skilled ParaView users to support AI research through flexible, hourly contract work. This is not a traditional job. You'll draw on your hands-on experience with scientific visualization, fluid dynamics simulation, or large dataset analysis to evaluate AI-generated content and provide feedback that helps AI better understand computational science tasks and HPC workflows. This is an ongoing, project-based opportunity you can take on alongside anything else you have going on. Who This Is For This is a good fit if you're an experienced ParaView user who has worked in or around roles like: - Computational Fluid Dynamics Engineer or Research Scientist - Aerospace Engineer or Applied Mathematician - HPC Specialist or Computational Scientist You should have solid experience with one or more of the following: - Scientific visualization, CFD post-processing, or large dataset analysis using ParaView - Fluid dynamics simulation, VTK workflows, or HPC data pipelines - Annotating or labeling simulation outputs and scientific datasets - Reviewing visualization results for accuracy, performance, or scientific consistency What You'll Do You'll use your experience with ParaView to create tool-related questions and review AI-generated responses for accuracy and relevance to real-world CFD and scientific visualization workflows. No prior AI or technical experience is required. Qualifications We're looking for people who have: - At least 1 year of hands-on experience with ParaView , whether through professional work or freelance projects - A working knowledge of CFD post-processing,

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