Freelance Machine Learning Engineer

Remote from: Romania
Salary, yearly, USD: 116,000
Department: Software Engineering
Employment type: Full Time,
Job posted: 25 May 2026
Apply before: 25 Jun 2026
Experience level: Midweight
Views / Applies: 17 / 3

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

Actively Hiring

AI Summary

Mindrift is seeking a freelance Machine Learning Engineer for project-based AI opportunities with leading tech companies. The role involves designing computational STEM problems, creating Python programming challenges, and verifying solutions. Ideal candidates have 5+ years of ML experience, expert Python skills, and familiarity with GenAI and MLOps. Tasks require 10-20 hours per week with compensation up to $58/hour. This is a non-permanent, remote position suitable for experienced ML specialists.

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 expert-level machine learning and Python skills, plus the ability to design original, computationally intensive problems. The high expertise and creative demands make it challenging, hence a 4.

Salary Analysis

AI Insight The offered salary of up to $58/hour equates to a yearly median of ~$120,640 based on 40-hour weeks, which is competitive for freelance ML engineers. The market range for similar roles in the US is $100k-$180k, so this offer is in the lower-mid range but reasonable for project-based work.

Key Skills

Machine Learning Python Data Science LLMs PyTorch TensorFlow SQL MLOps GenAI Statistical Analysis

Cover Letter Sample

Dear Hiring Team,

I am writing to express my interest in the Freelance Machine Learning Engineer opportunity at Mindrift. With over 5 years of hands-on ML experience and a strong background in Python programming, I have successfully delivered impactful projects in data science and AI. My expertise includes designing complex algorithms, working with frameworks like PyTorch and TensorFlow, and implementing MLOps practices.

I am particularly drawn to the challenge of creating original computational problems that push the boundaries of AI systems. My portfolio includes projects involving LLMs, RAG, and vector databases, aligning perfectly with your requirements. I am confident in my ability to contribute to your projects and ensure high-quality solutions.

Thank you for considering my application. I look forward to the opportunity to collaborate and discuss how my skills can add value to Mindrift's initiatives.

Sincerely,
[Your Name]

Possible Interview Questions

Can you describe a complex machine learning problem you solved and the approach you took?

I worked on a fraud detection system for a fintech company. I used gradient boosting with feature engineering on transactional data, achieving a 20% improvement in recall. I also implemented a real-time scoring pipeline using MLOps tools.

How would you design a computational problem that requires Python to solve and cannot be done manually?

I would create a problem involving large-scale matrix operations with random data, requiring optimization of a custom algorithm. For example, solving a constrained optimization problem with thousands of variables using scipy.optimize, where manual calculation is infeasible.

Explain your experience with LLMs and how you have used them in projects.

I have used LLMs for text summarization and question-answering systems. In one project, I implemented a RAG pipeline using LangChain and vector databases to provide accurate responses from a custom knowledge base.

What is your approach to verifying the correctness of a solution to a complex problem?

I write unit tests and use property-based testing to validate outputs. For machine learning, I cross-validate with multiple metrics and compare against baseline models. I also document the reasoning and assumptions clearly.

How do you stay updated with the latest developments in machine learning?

I follow top conferences like NeurIPS and ICML, read research papers on arXiv, and participate in Kaggle competitions. I also experiment with new frameworks and contribute to open-source projects.

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 STEM problems that simulate real scientific workflows
Create problems that require Python programming to solve
Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks)
Develop problems requiring non-trivial reasoning chains and creative problem-solving approaches
Verify solutions using Python with standard libraries (Numpy, Pandas, Scipy, scikit-learn)
Document problem statements clearly and provide verified correct answers

What we look for
This opportunity is a good fit for ML specialists with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:

5+ years of hands-on machine learning experience with proven business impact
Portfolio of completed projects and publications showcasing real-world problem-solving
Expert Python programming for data science (pandas, numpy, scipy, scikit-learn, statsmodels)
Expert statistical analysis and machine learning – deep understanding of algorithms, methods, and their practical applications
Expert with SQL and database operations for data manipulation and analysis
Experience with GenAI technologies (LLMs, RAG, prompt engineering, vector databases)
Understanding of MLOps practices and model deployment workflows
Knowledge of modern frameworks (TensorFlow, PyTorch, LangChain)
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 $58 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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