Freelance Mechanical Engineering Specialist with Python Expertise

Mindrift; Missouri; On-site; USD 75,768; Part time

Benefits offered by this job

Up to $55/hour

Fully remote

Flexible schedule

Contribute to AI systems

Job summary

A leading AI innovation firm is looking for experienced Mechanical Engineers with strong Python skills to train and evaluate AI models on complex mechanical engineering problems. The role emphasizes professional judgment and engineering rigor. Candidates should have a relevant degree and at least 3 years of experience in fields such as thermodynamics and mechanics. This flexible, fully remote, part-time freelance position pays up to $55/hour, allowing engineers to contribute to innovative AI projects.

Qualifications

• 3+ years professional or advanced academic experience in thermodynamics, heat transfer, or fluid mechanics.
• Experience in solid mechanics, dynamics, or vibration analysis.
• Ability to design computationally intensive mechanical engineering problems.

Responsibilities

• Design graduate- and industry-level mechanical engineering problems.
• Evaluate AI-generated solutions for correctness and logic.
• Validate analytical results using Python (NumPy, SciPy, Pandas).
• Improve AI reasoning to align with engineering standards.

Skills

Strong Python proficiency

Advanced English proficiency (C1+)

Mechanical design

Numerical validation

Problem-solving

Education

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

Job description

Overview

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

You may be asked to:

• 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 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+)
• Strong Python proficiency for numerical validation
• 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