AI engineer for large language models

This role focuses on training and evaluating large language models, leveraging deep machine learning expertise. We provide a platform that connects researchers and companies with a global pool of participants, enabling the collection of high‑quality, ethically sourced human behavioural data and feedback.

• review AI‑generated explanations of model architectures, loss functions, and backpropagation for technical accuracy.
• validate ML‑specific code (e.g., training loops, data preprocessing scripts, or model evaluations) for efficiency and correctness.
• provide high‑quality human feedback necessary to align models with human intent, safety, and helpfulness.
• critically assess how an AI model navigates complex chain‑of‑thought prompts and identify where the reasoning breaks down.
• conduct comparative testing between different model outputs based on specific technical taxonomies and performance metrics.

• a BS, MS, or PhD in Computer Science, Artificial Intelligence, Robotics, or a related quantitative field with a focus on Machine Learning.
• experience building, deploying, or fine‑tuning ML models in a production environment.
• professional-level understanding of neural network architectures (Transformers, CNNs, RNNs) and optimization techniques.
• hands‑on experience with Prompt Engineering, RLHF (Reinforcement Learning from Human Feedback), or RAG (Retrieval‑Augmented Generation) workflows.
• the ability to audit complex model logic, identify training data contamination, and evaluate mathematical proofs behind ML algorithms.
• high attention to detail in spotting hallucinations, biased outputs, or logical failures in AI-generated technical content.
• expert proficiency in PyTorch or TensorFlow/Keras.
• advanced Python (NumPy, Pandas, Scikit‑learn) and experience with Hugging Face Transformers.
• experience with AWS (SageMaker), Google Cloud (Vertex AI), or specialized tools like Weights & Biases and LangChain.
• familiarity with Pinecone, Milvus, or Weaviate for RAG evaluation.

• Competitive pay rates, flexible hours, and the ability to work from home.