Mechanical Engineer & Python Expert – Freelance AI Trainer

Mindrift; San Antonio (TX); On-site; USD 48,000 - 95,000; Full time

Job summary

Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. This project-based role involves designing computational engineering problems that require Python programming, running simulations, and verifying results with standard libraries such as NumPy and SciPy.

Tasks are 10–20 hours per week during active phases, with pay up to $69 per hour.

Qualifications

• Degree in Mechanical Engineering or related field.
• Python proficiency for numerical validation.
• 2+ years of professional experience: applied, research, or teaching experience is applicable.
• Understanding of practical engineering constraints and approximations.
• Strong written English (C1+).
• Professional certifications (e.g., CMME, SAS Certifications, CAP) and experience in international or applied projects are an advantage

Responsibilities

• Design original computational engineering problems that simulate real engineering workflows.
• Create problems requiring Python programming to solve engineering calculations and simulations.
• Ensure problems are computationally intensive and require numerical methods or iterative solutions.
• Develop problems involving system design, optimization, and analysis.
• Base problems on real research challenges or practical applications from engineering practice.
• Verify solutions using Python with standard engineering libraries.
• Document problem statements clearly and provide verified correct answers

Skills

Python

Numerical methods

English proficiency

Education

Bachelor's degree in Mechanical Engineering

Tools

MATLAB

R

C

SQL

NumPy

Pandas

SciPy

Job description

Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems.

What This Opportunity Involves

Participation is project-based, not permanent employment.

• Design original computational engineering problems that simulate real engineering workflows;


• Create problems requiring Python programming to solve engineering calculations and simulations;


• Ensure problems are computationally intensive and require numerical methods or iterative solutions;


• Develop problems involving system design, optimization, and analysis;


• Base problems on real research challenges or practical applications from engineering practice;


• Verify solutions using Python with standard engineering libraries;


• Document problem statements clearly and provide verified correct answers

What We Look For

This opportunity is a good fit for engineers with an experience in python open to part-time, non-permanent projects.

Ideally, contributors will have:

• Degree in Mechanical Engineering 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;


• Understanding of practical engineering constraints and approximations;


• Strong written English (C1+);


• Professional certifications (e.g., CMME, SAS Certifications, CAP) and experience in international or applied projects are an advantage

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.

Compensation

On this project, contributors can earn up to $69 per hour equivalent , depending on their level and pace of contribution.

Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.