About the job
Please submit your CV in English and specify your English proficiency level.
This freelance, project-based contract with toloka-ai (via Mindrift) offers physicists the chance to shape and evaluate AI systems for leading technology companies. The work centers on testing, improving, and designing computational challenges that reflect real research in physics. This is not a permanent employment offer.
Key Responsibilities
- Design computational physics problems that align with real research workflows.
- Create programming challenges requiring Python solutions, often using Numpy, SciPy, or Sympy.
- Develop problems that are computationally intensive and cannot be solved manually within a reasonable time.
- Craft advanced scenarios in mechanics, electromagnetism, thermodynamics, and quantum mechanics.
- Base scenarios on genuine research issues or practical physics applications.
- Validate solutions using Python and standard simulation tools.
- Document each problem clearly and provide verified answers.
Requirements
- Degree in Physics (Theoretical, Experimental, or Computational) or a related field.
- Proficiency in Python for numerical validation. Experience with MATLAB, R, C, SQL, Numpy, Pandas, or SciPy is a plus.
- At least 2 years of applied research or teaching experience.
- Background in numerical simulation methods.
- Ability to design problems that mirror authentic research workflows in physics.
- Creative problem-solving skills across diverse physics topics.
- Knowledge of modeling and approximation techniques.
- Strong written English skills (C1 level or higher).
Project Process
Steps include: Application, Qualification Process, Project Participation, Task Completion, and Payment.
Time Commitment
Project tasks typically require 10–20 hours per week during active phases. Actual workload may vary with project needs.
Compensation
Contributors can earn up to $76 per hour, depending on expertise and pace. Compensation varies by project scope and complexity. Other projects on the platform may offer different earning levels based on requirements.

