This is a remote, project-based role for reliability, quality, process and test engineers with 3+ years of full time experience who use statistics in their work. You will author realistic engineering analysis problems drawn from your work, covering designed experiments, statistical process control, and reliability and failure data, and work each one through to a reference answer that frontier AI labs use to test model judgment. Work is fully async with no fixed hours, a minimum of 10 hours per week and no maximum, and you can scale up or down week to week. This is an independent contractor role with ongoing project work, paid weekly via Stripe, with no screen recording, keystroke monitoring, or idle timers. We are not looking for site reliability engineers or software engineers.
Responsibilities
- Author realistic engineering analysis problems drawn from your work: designed experiments, process control, reliability and failure data
- Work each problem through to a reference answer, with the reasoning behind every step
- Catch the analysis mistakes that look reasonable but only a practitioner would spot
Requirements
- Degree in engineering, physics or statistics
- 3+ years full time in a reliability, quality, process or test role (internships and school don't count)
- Hands-on experience with design of experiments, statistical process control or reliability analysis
- Comfortable with Minitab, JMP, Python or R
- Strong written English and able to explain an analysis clearly
- Able to commit at least 10 hours per week
Preferred Qualifications
- Master's degree in engineering or statistics
- Experience with capability studies, measurement system analysis, life data analysis or uncertainty quantification
Why Apply
- Work stays in your specialty, judged on engineering judgment rather than volume
- Set your own hours and scale up or down week to week
- Weekly pay via Stripe
- Your judgment shapes how the next generation of AI handles engineering analysis