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Freelance Energy Engineer with Python Experience - AI Trainer

Mindrift · Hamburg, Alemanha · Remote

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Description

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 rigorous energy engineering problems reflecting professional practice;
  • Evaluate AI solutions for correctness, assumptions, and constraints;
  • Validate calculations or simulations using Python (NumPy, Pandas, SciPy);
  • Improve AI reasoning to align with industry-standard logic;
  • Apply structured scoring criteria to multi-step problems.

What we look for

This opportunity is a good fit for energy engineers with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have: 

  • Degree in Energy Engineering or related fields, e.g. Electrical Engineering, Power Systems Engineering, Renewable Energy Engineering, Electronics etc.
  • 3+ years of professional energy engineering experience
  • Strong written English (C1/C2)
  • Strong Python proficiency for numerical validation
  • Stable internet connection 

Professional certifications (e.g., PE, CEng, EMP, CEM) 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.

Payment

  • Paid contributions, with rates up to $50/hour* 
  • Fixed project rate or individual rates, depending on the project
  • Some projects include incentive payments

*Note: Rates vary based on expertise, skills assessment, location, project needs, and other factors. Higher rates may be offered to highly specialized experts. Lower rates may apply during onboarding or non-core project phases. Payment details are shared per project.