Optical Engineer with Python - Freelance AI Trainer

Benefits

Additional Information

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 original computational physics problems that simulate real physics research workflows; Create problems requiring Python programming to solve (using Numpy, SciPy, Sympy); Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks); Develop problems requiring non-trivial reasoning chains in mechanics, electromagnetism, thermodynamics, and quantum mechanics; Base problems on real research challenges or practical applications from physics practice; Verify solutions using Python with standard physics simulation libraries; Document problem statements clearly and provide verified correct answers. What we look for This opportunity is a good fit for optical engineers with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have: Degree in Physics (Theoretical, Experimental, or Computational) or related fields; Python proficiency for numerical validation. MATLAB, R, C, SQL, Numpy, Pandas, SciPy, domain-specific libraries, Stata or knowledge of any programming language can be equivalent; 2+ years of professional experience: applied, research, or teaching experience is applicable; Experience with numerical simulation methods; Ability to design problems that mirror real physics research workflows; Creative thinking in problem design across diverse physics areas; Familiarity with physics modeling and approximation techniques; Strong written English (C1+). 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.