AI Engineer/ML Engineer - Senior Developers - AI Training - UK

• Evaluate LLM architecture logic: review AI-generated explanations of model architectures, loss functions, and backpropagation for technical accuracy.
• Audit code & notebooks: validate ML-specific code (training loops, data preprocessing scripts, model evaluations) for efficiency and correctness.
• Refine RLHF frameworks: provide high-quality human feedback to align models with human intent, safety, and usefulness.
• Analyze model reasoning: assess how an AI model navigates complex chain-of-thought prompts and identify where reasoning breaks down.
• Benchmark performance: conduct comparative testing between different model outputs based on technical taxonomies and performance metrics.

• Education: a BS, MS, or PhD in Computer Science, Artificial Intelligence, Robotics, or a related quantitative field with a focus on Machine Learning.
• Professional Experience: experience building, deploying, or fine-tuning ML models in a production environment.
• Deep Learning Mastery: professional-level understanding of neural network architectures (Transformers, CNNs, RNNs) and optimization techniques.
• LLM Specialization: hands-on experience with Prompt Engineering, RLHF, or RAG workflows.
• Technical Rigor: ability to audit complex model logic, identify training data contamination, and evaluate mathematical proofs behind ML algorithms.
• Analytical Critique: high attention to detail in spotting hallucinations, biased outputs, or logical failures in AI-generated technical content.

• Pay rate up to $80 per hour; many tasks require one hour of uninterrupted work, though many are shorter.
• As a participant, you will be invited to join Prolific after a quick assessment and will be paid to train and evaluate AI models.
• Flexible hours and the ability to work from home.

AI & Machine Learning Engineer - AI Training at Prolific. Prolific is building the biggest pool of quality human data in the world. Over 35,000 AI developers, researchers, and organizations use Prolific to gather data from paid study participants with a wide variety of experiences, knowledge, and skills.