About the job
Kindly submit your CV in English and specify your English proficiency level.
Mindrift bridges the gap between talented professionals and project-based AI initiatives for top-tier tech firms, emphasizing the testing, evaluation, and enhancement of AI systems. This is a project-based role, not permanent employment.
Key Responsibilities
Each project presents distinct tasks; contributors may:
- Create comprehensive physics problems that mirror real-world applications;
- Assess AI solutions for accuracy, underlying assumptions, and limitations;
- Verify calculations or simulations using Python libraries such as NumPy, Pandas, and SciPy;
- Enhance AI reasoning to conform to industry-standard logic;
- Utilize structured scoring criteria for multi-step challenges.
Ideal Candidate Profile
This position is ideal for physicists experienced in Python who are open to part-time, non-permanent roles. Preferred qualifications include:
- A degree in Physics or related disciplines, such as Engineering Physics, Thermodynamics, Statistical Mechanics, Optics, or Acoustics;
- A minimum of 3 years of professional experience in physics;
- Strong command of written English (C1/C2 level);
- Proficient in Python for numerical validation;
- A reliable internet connection.
Professional certifications (e.g., CPhys, EurPhys, MInstP) and experience with international or applied projects are considered advantageous.
Process Overview
Apply → Pass qualifications → Join a project → Complete tasks → Receive payment.
Project Commitment
During active phases, tasks are estimated to require approximately 10–20 hours per week, based on project specifications. This is an estimate and not a guaranteed workload, applicable only during active project phases.
Compensation
- Competitive pay for contributions, with rates up to $10/hour*;
- Fixed project rate or individual rates based on project requirements;
- Some projects may offer incentive payments.
*Note: Compensation rates may vary depending on expertise, skills assessment, location, project requirements, and other criteria. Highly specialized experts may receive higher rates, while lower rates might apply during onboarding or non-core project phases. Payment details are disclosed per project.

