Key skills
AIMachine LearningMLMLOpsProblem SolvingCollaboration
About this role
Role Overview
- Review and refine AI generated outputs on a variety of machine learning and AI topics
- Evaluate responses for technical accuracy, ML best practices, and compliance with industry standards
- Draft realistic ML engineering scenarios, including model evaluation, deployment approaches, data pipeline design, scaling challenges, interpretability, and ethical considerations
- Create variations of the same scenario from different roles, such as ML engineer, data scientist, business stakeholder, or compliance advisor
- Identify gaps, misinterpretations, or oversimplified reasoning in AI generated content
- Assess and improve AI reasoning around structured problem solving, edge cases, and application of theoretical concepts
Requirements
- A machine learning engineer, data scientist, or AI engineer with several years of hands-on experience
- Based in the EU or UK
- Experienced across the ML workflow: model development, evaluation, tuning, deployment and monitoring
- Comfortable identifying limitations in data, experimental design, model selection, fairness, or explainability
- Familiar with current ML frameworks, MLOps best practices, and ethical or AI governance standards
- Available 8 to 20 hours per week
- Able to start in the coming weeks
Benefits
- Flexible, part-time hours
- Fully remote opportunity
- Apply your ML expertise to advance the field of AI
- Contribute to the performance of widely used AI systems
- Clear scope and structured onboarding
- Potential for long-term collaboration based on performance