Freelance Energy Engineer with Python Experience - AI Trainer

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 paidProject 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 $38/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.Originally posted on Himalayas

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 paidProject 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 $38/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.Originally posted on Himalayas