Optical Engineer with Python – Freelance AI Trainer

Remote from: Italy
Salary, yearly, USD: 58,000
Department: Software Engineering
Employment type: Full Time,
Job posted: 28 May 2026
Apply before: 28 Jun 2026
Experience level: Midweight
Views / Applies: 23 / 1

Mindrift connects AI experts and clients to advance Generative AI models.

Actively Hiring

AI Summary

This freelance role involves designing original computational physics problems for AI training, requiring Python proficiency and a physics degree. Contributors create problems simulating real research workflows, focusing on mechanics, electromagnetism, thermodynamics, and quantum mechanics. The position is project-based with an estimated 10-20 hours per week during active phases, paying up to $29 per hour. Ideal candidates have 2+ years of professional experience and strong written English (C1+). This is a non-permanent opportunity to work with leading tech companies on improving AI systems.

Role DNA

Job Complexity

Easy Hard

Pace & Pressure

Relaxed Fast-paced

Autonomy Level

Guided Full Ownership

Communication Load

Independent Highly Collaborative

AI Insight The role requires advanced physics knowledge and Python programming, making it challenging. However, it is freelance and project-based, allowing for some flexibility.

Salary Analysis

AI Insight The offered salary is $58,000 per year, which is below the typical US market range for optical engineers ($60,000-$120,000). However, this is a part-time freelance role, so the hourly rate of up to $29 may be competitive for the flexible nature of the work.

Key Skills

Python NumPy SciPy SymPy Computational Physics Optical Engineering Problem Design Numerical Simulation AI Training Freelance

Cover Letter Sample

Dear Hiring Team,

I am writing to express my interest in the Optical Engineer with Python - Freelance AI Trainer position. With a degree in Physics and over 2 years of experience in applied research, I possess strong Python programming skills using libraries like NumPy, SciPy, and SymPy. My background in designing computational physics problems aligns perfectly with the requirements of this role.

I have experience creating problems that simulate real physics research workflows, particularly in mechanics and electromagnetism. I am comfortable with numerical simulation methods and can ensure problems are computationally intensive yet solvable within reasonable timeframes.

I am excited about the opportunity to contribute to AI training and look forward to the possibility of working with your team. Thank you for considering my application.

Sincerely, [Your Name]

Possible Interview Questions

Describe your experience with Python in solving computational physics problems. Which libraries do you use most frequently?

I have used Python extensively in my research, primarily with NumPy for array operations, SciPy for numerical integration and optimization, and SymPy for symbolic mathematics. For example, I developed a simulation of electromagnetic wave propagation using these libraries.

Can you provide an example of a computational physics problem you designed that mirrors a real research workflow?

I created a problem simulating the heat equation in a 2D plate with variable boundary conditions, requiring the use of finite difference methods and eigenvalue decomposition. This mirrors real thermal analysis in engineering.

How do you ensure that your problems are computationally intensive and cannot be solved manually within reasonable timeframes?

I design problems with large parameter spaces or iterative calculations that require numerical methods. For instance, solving a system of coupled differential equations with 1000+ time steps makes manual solution impractical.

What is your approach to documenting problem statements and verifying correct answers?

I provide clear, step-by-step problem statements with all necessary parameters and assumptions. For verification, I write a separate Python script that solves the problem and checks against the expected output, ensuring the solution is correct and reproducible.

How do you stay updated with the latest developments in physics and computational methods?

I regularly read journals like Physical Review and attend conferences. I also follow online communities like Stack Exchange and GitHub repositories for new simulation libraries and techniques.

Please submit your CV in English and indicate your level of English proficiency.

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

What this opportunity involves

While each project involves unique tasks, contributors may:

Design original computational physics problems that simulate real physics research workflows;
Create problems requiring Python programming to solve (using Numpy, SciPy, Sympy);
Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks);
Develop problems requiring non-trivial reasoning chains in mechanics, electromagnetism, thermodynamics, and quantum mechanics;
Base problems on real research challenges or practical applications from physics practice;
Verify solutions using Python with standard physics simulation libraries;
Document problem statements clearly and provide verified correct answers.

What we look for

This opportunity is a good fit for optical engineers with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:

Degree in Physics (Theoretical, Experimental, or Computational) 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;
Experience with numerical simulation methods;
Ability to design problems that mirror real physics research workflows;
Creative thinking in problem design across diverse physics areas;
Familiarity with physics modeling and approximation techniques;
Strong written English (C1+).

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 $29 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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