Machine Learning Expert, Python, GenAI And SQL

The work

You will create original text-based computational machine learning and STEM problems that reflect real scientific workflows. Problems should require Python programming and meaningful reasoning rather than being solvable manually in a reasonable amount of time.

You will also write solution paths, run reproducible checks, and confirm that the answers are correct. The work includes prompt and response writing, text generation, question answering, evaluation, and programming or coding tasks.

• Design computational ML and STEM problems with clear solution paths.
• Write Python-based solutions and validate outputs with NumPy, Pandas, SciPy, and scikit-learn.
• Check that problems are computationally intensive, accurate, and scientifically meaningful.
• Document problem statements and validated answers clearly in written English.

What it pays and takes

This is a part-time, project-based contractor role for an expert-level machine learning specialist. The project description calls for about 10 to 20 hours per week during active phases, while the role listing indicates 20 or more hours per week.

• Pay: $15 to $40 USD per hour, with the listed hourly rate of $40.
• Location: Global; applicants may work from any location.
• Language: Fluent written English at C1 level or equivalent.
• Experience: At least five years of hands-on machine learning experience with demonstrated business impact.
• Python: Expert data science skills with NumPy, Pandas, SciPy, and scikit-learn; statsmodels is a bonus.
• Statistics and ML: Expert statistical analysis skills and a strong understanding of algorithms and practical trade-offs.
• Problem design: Ability to create original computational STEM and ML problems with clear solution paths.
• Validation: Experience verifying solutions with reproducible Python code and correct outputs.
• SQL: Strong skills with joins, aggregations, window functions, and database data manipulation.
• GenAI: Experience with LLMs, retrieval-augmented generation, prompt engineering, and vector databases.
• MLOps: Familiarity with packaging, reproducibility, monitoring basics, and deployment workflows.
• Frameworks: Experience with TensorFlow or PyTorch; LangChain is a bonus.

How it works

Apply on OpenTrain. The employer reviews applications there.

About AI training work

AI training work uses human-written examples, ratings, and technical checks to improve how artificial intelligence systems respond and reason. People with deep technical experience are needed to create reliable problems, assess model outputs, and verify that training data is correct.],