Please submit your CV in English and indicate your level of English proficiency.
Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation isproject-based, not permanent employment.
What this opportunity involves
While each project involves unique tasks, contributors may:
* Design graduate- and industry-level mechanical engineering problems grounded in real practice.
* Evaluate AI-generated solutions for correctness, assumptions, and engineering logic.
* Validate analytical or numerical results using Python (NumPy, SciPy, Pandas).
* Improve AI reasoning to align with first principles and accepted engineering standards.
* Apply structured scoring criteria to assess multi-step problem solving.
What we look for
This opportunity is a good fit for mechanical engineers with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:
* Degree in Mechanical Engineering or related fields, e.g. Thermodynamics, Fluid Mechanics, Mechanical Design, Computational Mechanics, etc.
* 3+ years of professional mechanical engineering experience
* Strong written English (C1/C2)
* Strong Python proficiency for numerical validation
* Stable internet connection
Professional certifications (e.g., PE, CEng, PMP) and experience in international or applied projects are an advantage.
How it works
Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid
Project time expectations
For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active.
Compensation
On this project, contributors can earn up to $35 per hour equivalent, depending on their level and pace of contribution.
Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.