Freelance Energy Engineer And Python Expert AI Trainer

Job description / Role

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 is project-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 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 $40/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.