Job Details

Overview 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 physics 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 problemsWhat We Look For This opportunity is a good fit for physicists with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:Degree in Physics or related fields, e.g. Engineering Physics, Thermodynamics, Statistical Mechanics, Optics and Acoustics, etc.3+ years of professional physics experienceStrong written English (C1/C2)Strong Python proficiency for numerical validationStable internet connectionProfessional certifications (e.g., CPhys, EurPhys, MInstP) 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 $55/hour*Fixed project rate or individual rates, depending on the projectSome projects include incentive paymentsNote: 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#J-18808-Ljbffr