Python Machine Learning Quality Assurance Lead

About OpenTrain

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• Remote contract opportunity for contributors based in the United States
• Part-time schedule requiring 20 or more hours per week
• Hourly pay of $120 USD

About AI Training and Data Labeling

AI training is the human side of building artificial intelligence. Specialists review model outputs, evaluate technical work, write feedback, and prepare examples that help AI systems become more accurate, reliable, and useful.

In this role, your Python and machine learning judgment will help assess generated code, workflows, explanations, and contributor work against detailed project standards.

• Work directly on the quality of modern AI systems
• Use technical expertise to evaluate and improve model-generated content
• Contribute to flexible, remote work in a fast-growing technology field

The Role

OpenTrain is seeking an intermediate Python Machine Learning Quality Assurance Lead to review AI-generated Python code, machine learning workflows, model explanations, and trainer QA work. You will monitor quality, evaluate outputs against project guidelines and rubrics, provide clear written feedback, and help contributors maintain high standards across Python machine learning training work.

The role also includes answering questions about Python syntax, package usage, data leakage, model validation, metrics, reproducibility, notebooks, and rubric interpretation. You will support contributor communication, documentation, onboarding materials, calibration tasks, and process improvements for technical review workflows.

• Employment type: Contractor and part-time
• Location: United States
• Language: English
• Experience level: Intermediate
• Time requirement: 20+ hours per week
• Pay: $120 USD per hour

What You’ll Do

You will combine hands-on Python expertise with practical machine learning evaluation judgment. Your reviews should identify both obvious technical errors and subtle issues that could make training data misleading or difficult to reproduce.

• Review AI-generated Python code, ML pipelines, preprocessing steps, model training workflows, evaluation logic, and explanations for correctness and reproducibility.
• Spot-check work for data leakage, statistical validity, debugging accuracy, formatting, readability, maintainability, and instruction-following.
• Provide precise feedback to contributors and escalate recurring or critical quality issues.
• Answer questions about Python syntax, package usage, model validation, metrics, notebooks, reproducibility, and rubric interpretation.
• Update guidance, trackers, FAQs, examples, honeypots, and onboarding materials.
• Support onboarding and training calls for Python ML contributors.
• Help maintain scalable QA processes for remote technical teams.
• Support contributor communication, calibration tasks, documentation, and process improvements.

Required Skills and Experience

You should be able to evaluate technical content against detailed rubrics and explain issues clearly in written English. Practical experience with AI training, data annotation, LLM evaluation, code QA, ML QA, or rubric-based technical review is a strong plus.

• Strong Python fundamentals, including data structures, functions, classes, iterators, comprehensions, exception handling, virtual environments, package management, testing, and debugging.
• Strong machine learning knowledge across supervised and unsupervised learning, feature engineering, train/test splits, cross-validation, model selection, data leakage, regression, classification, clustering, metrics, bias and variance, regularization, and reproducibility.
• Strong Python debugging and package-management knowledge.
• Practical judgment when evaluating machine learning methodology and reproducibility.
• Ability to identify flawed methodology, incorrect metrics, hallucinated APIs, misleading conclusions, and incomplete explanations.
• Clear English communication for precise technical feedback and team coordination.
• Experience leading or supporting remote teams of trainers, reviewers, engineers, data scientists, or machine learning researchers is preferred.
• Experience with AI training, data annotation, LLM evaluation, code QA, ML QA, or rubric-based technical review is a strong plus.

Who Should Apply

This opportunity is suited to a Python and machine learning professional who enjoys detailed technical review, debugging, documentation, and helping other contributors improve. It is especially relevant if you have coordinated remote technical contributors or worked with structured evaluation rubrics.

The work is remote and part time, making it a potential fit for professionals who can commit at least 20 hours each week while contributing to the development of AI systems.

• Python developers with strong machine learning knowledge
• Machine learning practitioners experienced with evaluation and reproducibility
• Technical reviewers, QA specialists, or AI training contributors
• Engineers, data scientists, or ML researchers comfortable giving written feedback
• Remote team leads or coordinators with technical contributor experience

How to Apply Through OpenTrain

Create a free OpenTrain account, build your profile, and apply for this contractor opportunity in minutes. OpenTrain helps people discover and grow careers in AI training, where technical reviewers play a direct role in improving how AI systems perform.

• Confirm that you are based in the United States and can work in English.
• Review the 20+ hour weekly commitment and $120 per hour rate.
• Highlight your Python, machine learning, QA, evaluation, and remote coordination experience.
• Submit your application through OpenTrain.