Mechanical & Aerospace Test and Reliability Engineer

About the role

Use your hands-on experience in mechanical and aerospace engineering to write research-level problems for AI models. Remote, flexible contract work.

AfterQuery works with leading AI labs to build the expert data that tests and trains AI models. We're looking for test and reliability engineers who work with real test data: the performance trials, vibration and modal surveys, rig or flight tests, and failure investigations you have run and written up.

Requirements

• Technical: Working knowledge of Python (MATLAB is a plus) for reducing and analyzing your own test data.

Preferred

• Background: 3 or more years of hands-on test, commissioning or condition-monitoring work, with a Bachelor's, Master's or PhD in mechanical or aerospace engineering.
• Hands-on work with real data, rather than pure CAD or design, simulation only, or management roles.

Contract and pay

Flexible, independent-contractor work: $300 per approved task, about 6 hours each (roughly $50 per hour), with no cap on how many tasks you take on.

All accepted experts undergo standard background and identity verification.

Why apply

• $300 per approved task (roughly $50 per hour)
• Fully remote and flexible, with no fixed weekly schedule

Responsibilities

• Write research-level problems in your area of expertise
• Work independently and manage your own time
• Keep your work accurate, clear and well documented

Required qualifications

• Hands-on experience working with your own real test data in Python or a similar language
• Able to write clearly about technical work in your field
• Able to work independently and manage your own time. This is flexible, task-based work with no fixed weekly schedule

Preferred qualifications

• 3+ years of hands-on test, commissioning or condition-monitoring work, with a degree in mechanical or aerospace engineering
• Wrote acceptance or performance test reports; experience with ISO 10816/20816, API 670 or ASME PTC codes; Chartered Engineer or PE
• Public code, a thesis or papers that show your technical work
• Prior experience in data annotation, data labeling or AI/ML evaluation work