About the job
We invite you to submit your resume in English, clearly indicating your level of English proficiency.
Mindrift connects talented specialists with project-based AI opportunities for top-tier tech firms, focusing on testing, evaluating, and enhancing AI systems. Note: This role is project-based and does not offer permanent employment.
Role Overview:
Each project presents unique challenges, including but not limited to:
- Designing original computational physics problems that reflect genuine research workflows;
- Formulating problems requiring Python programming solutions (utilizing libraries such as Numpy, SciPy, and Sympy);
- Creating problems that are computationally demanding, ensuring they cannot be solved manually within practical timeframes (days or weeks);
- Developing intricate problems necessitating advanced reasoning in mechanics, electromagnetism, thermodynamics, and quantum mechanics;
- Grounding problems in actual research dilemmas or applicable real-world physics scenarios;
- Verifying solutions through Python using standard physics simulation libraries;
- Writing clear and comprehensive problem statements along with verified correct answers.
Candidate Profile:
This opportunity is ideal for individuals with a physics background and Python expertise, seeking part-time, non-permanent projects. The ideal candidates will possess:
- A degree in Physics (Theoretical, Experimental, or Computational) or related disciplines;
- Proficiency in Python for numerical validation (knowledge of MATLAB, R, C, SQL, Numpy, Pandas, SciPy, or similar programming languages is also acceptable);
- A minimum of 2 years of relevant experience, including applied, research, or teaching roles;
- Familiarity with numerical simulation techniques;
- Capability to design problems that emulate authentic physics research workflows;
- Creative problem-solving skills across various physics domains;
- Solid command of written English (C1+ level).
Project Workflow:
To participate, follow these steps: Apply → Pass qualifications → Join a project → Complete tasks → Receive compensation.
Expected Commitment:
For this project, contributors can expect to dedicate approximately 10–20 hours per week during active phases, contingent upon project requirements. Note that this is an estimate and not a guaranteed workload.
Compensation:
Participants in this project can earn up to $76 per hour, depending on their proficiency and contribution pace. Compensation may vary by project based on its scope, complexity, and the expertise required. Please be aware that other projects on the platform may offer different compensation rates based on their specific needs.

