About the job
Please submit your CV in English and indicate your English proficiency level.
Mindrift connects skilled professionals with project-based AI work for leading technology companies. Projects focus on assessing, evaluating, and improving AI systems. Participation is on a project basis and does not constitute permanent employment.
Role overview
This freelance, remote position is for a Material Scientist with Python expertise to help train AI systems. Work centers on developing and validating engineering challenges, with projects varying in scope and focus. Contributors may:
- Create original materials and engineering problems based on real-world workflows
- Design problems that involve Python programming for calculations and simulations
- Develop computationally intensive problems requiring numerical methods or iterative solutions
- Build challenges related to system design, optimization, and analysis
- Base problems on genuine research questions or practical engineering scenarios
- Validate solutions using Python and standard engineering libraries
- Document problem statements with clear, accurate answers
Requirements
- Degree in Material Science or a related field
- Proficiency in Python for numerical validation; experience with MATLAB, R, C, SQL, Numpy, Pandas, SciPy, Stata, or domain-specific libraries is also accepted
- At least 2 years of professional experience (applied, research, or teaching)
- Strong understanding of practical engineering constraints and approximations
- Excellent written English (C1 level or above)
Project process
- Apply
- Pass qualifications
- Join a project
- Complete assigned tasks
- Receive payment
Time commitment
Active project phases usually require about 10–20 hours per week. Actual workload depends on project needs and is not guaranteed.
Compensation
Contributors may earn up to $45 per hour, depending on expertise and task completion speed. Pay rates vary by project according to complexity, scope, and required skills. Other projects on the platform may offer different compensation based on their requirements.
