Mechanical Engineer with Python Experience - Freelance AI Trainer

Mindrift

Town of Florida (NY)

Remote

USD 75,768

Part time

14 days+
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Benefits offered by this job

Earn up to $55/hour
Fully remote, flexible work
Contribute to innovative AI solutions

Job summary

A leading AI innovation firm is seeking a Mechanical Engineer with strong Python skills to evaluate AI models and design engineering problems. This fully remote, part-time freelance role offers up to $55/hour. The ideal candidate holds a Bachelor's, Master's, or PhD in Mechanical Engineering, has advanced Python proficiency, and possesses expertise in thermodynamics and mechanical design. Join us to contribute to the future of AI systems reasoning about mechanical engineering.

Qualifications

  • 3+ years of experience in Thermodynamics, Heat Transfer, Fluid Mechanics.
  • Experience with Solid Mechanics, Dynamics & Vibration.
  • Capable of designing computationally intensive problems.

Responsibilities

  • Design mechanical engineering problems grounded in real practice.
  • Evaluate AI-generated solutions for correctness.
  • Improve AI reasoning to align with first principles.

Skills

Python proficiency
Mechanical Engineering problems designing
Analytical validation
Advanced English proficiency

Education

Bachelor's, Master's, or PhD in Mechanical Engineering or closely related field

Tools

Python (NumPy, SciPy, Pandas)

Job description

Mechanical Engineer with Python Experience – Freelance AI Trainer

2 days ago Be among the first 25 applicants

This opportunity is only for candidates currently residing in the specified country. Your location may affect eligibility and rates. Please submit your resume in English and indicate your level of English.

At Mindrift, innovation meets opportunity. We believe in using the power of collective intelligence to ethically shape the future of AI.

What We Do

The Mindrift platform connects specialists with AI projects from major tech innovators. Our mission is to unlock the potential of Generative AI by tapping into real‑world expertise from across the globe.

The Role

We are seeking experienced Mechanical Engineers with strong Python skills to train and evaluate AI models on complex, real‑world mechanical engineering problems. This role focuses on professional judgment and engineering rigor, not data labeling or traditional software development.

What You’ll Do
  • Design graduate‑ and industry‑level mechanical engineering problems grounded in real practice
  • Evaluate AI‑generated solutions for correctness, assumptions, and engineering logic
  • Validate analytical or numerical results using Python (NumPy, SciPy, Pandas)
  • Improve AI reasoning to align with first principles and accepted engineering standards
  • Apply structured scoring criteria to assess multi‑step problem solving
How to Apply

Apply with your resume (English). Complete a short qualification process and get matched to projects aligned with your specialization.

Effort Estimate

Tasks for this project are estimated to take 6-10 hours to complete, depending on complexity. This is an estimate and not a schedule requirement; you choose when and how to work. Tasks must be submitted by the deadline and meet the listed acceptance criteria to be accepted.

Requirements
  • Bachelor's, Master's, or PhD in Mechanical Engineering or closely related field
  • Strong Python proficiency for numerical validation
  • 3+ years of professional or advanced academic experience in one or more of:
    • Thermodynamics, Heat Transfer, Fluid Mechanics
    • Solid Mechanics, Dynamics & Vibration
    • Mechanical Design, Machine Elements
    • FEA, CFD, Computational Mechanics
    • Manufacturing Processes, CAD/CAE, Thermal Systems
  • Advanced English proficiency (C1+)
  • Ability to design non‑trivial, computationally intensive problems
Benefits

Why Join

  • Earn up to $55/hour for your expertise
  • Fully remote, flexible, part‑time freelance work
  • Contribute to how future AI systems reason about mechanical engineering
  • Work on technically rigorous, non‑routine problems
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