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

Role overview This is a paid participant opportunity for senior AI and machine learning engineers based in Liverpool who want to apply their technical depth to shaping the next generation of large language models. The work centers on training and rigorously evaluating model outputs through expert human judgment rather than writing production systems. It is a flexible, remote-friendly engagement suited to practitioners who enjoy analytical critique work alongside their primary roles.

Responsibilities - Review AI-generated explanations of model architectures, loss functions, and backpropagation for technical correctness. - Audit ML code such as training loops, preprocessing scripts, and evaluation notebooks for efficiency and accuracy. - Provide structured human feedback that supports reinforcement learning from human feedback (RLHF) workflows aimed at alignment, safety, and helpfulness. - Analyze chain-of-thought reasoning from AI systems and pinpoint where logical chains break down. - Run comparative benchmarks across model outputs using defined technical taxonomies and performance metrics.

Requirements - BS, MS, or PhD in Computer Science, Artificial Intelligence, Robotics, or a related quantitative discipline with a machine learning focus. - Hands-on professional experience building, deploying, or fine-tuning machine learning models in production environments. - Deep familiarity with neural network architectures such as Transformers, CNNs, and RNNs, along with modern optimization techniques. - Practical experience with prompt engineering, RLHF, or retrieval-augmented generation (RAG) pipelines. - Strong analytical instincts for spotting hallucinations, bias, contamination, or flawed mathematical reasoning in AI-generated content.

Nice to have - Expert proficiency with PyTorch or TensorFlow/Keras, plus advanced Python skills across NumPy, Pandas, and Scikit-learn. - Familiarity with Hugging Face Transformers and vector databases such as Pinecone, Milvus, or Weaviate for RAG evaluation. - Exposure to cloud MLOps tooling such as AWS SageMaker, Google Vertex AI, Weights & Biases, or LangChain.

Benefits and work setup - Hourly compensation reaching up to $80 for tasks leveraging this level of expertise. - Fully remote, flexible scheduling with paid tasks generally capped at one uninterrupted hour. - Short onboarding path after passing a brief skills assessment.