Mechanical Engineer & Python Expert – Freelance AI Trainer

Mindrift

Colorado

On-site

USD 56,481 - 95,054

Full time

14 days+

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Job summary

Mindrift connects specialists with project-based AI opportunities for leading tech companies. Contributors work on Python-driven engineering problems, test solutions, and verify numerical accuracy in real-world tasks.

This role emphasizes open projects, part-time involvement, and preparation of clear problem statements with validated answers. English proficiency and relevant engineering background are required for rigorous collaboration.

Qualifications

  • Degree in Mechanical Engineering or related field.
  • Proficiency in Python for numerical validation; MATLAB, R, C, SQL, NumPy, Pandas, SciPy or related libraries may be equivalent.
  • 2+ years of professional experience: applied, research, or teaching experience.
  • Strong written English (C1+).
  • Certifications (e.g., CMME, SAS, CAP) and international/applied project experience are an asset.

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 programming
Numerical validation
NumPy
Pandas
SciPy
MATLAB
R
C
SQL
English proficiency

Education

Bachelor’s degree in Mechanical Engineering or related field

Tools

MATLAB
R
C
SQL

Job description

Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation isproject-based, not permanent employment.

What This Opportunity Involves

While each project involves unique tasks, contributors may:

  • 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
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.

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