AI Engineer/ML Engineer - Senior Developers - AI Training - Columbus, US

Role overview This opportunity invites experienced AI and machine learning engineers to join a paid expert network that supports the training and evaluation of large language models. Work is task-based and remote, focused on applying deep technical judgment to audit, critique, and improve model behavior rather than shipping production systems.

Responsibilities - Review AI-generated explanations of model architectures, loss functions, and backpropagation for technical accuracy - Audit ML code and notebooks, including training loops, preprocessing scripts, and evaluation pipelines, for correctness and efficiency - Supply high-quality human feedback used to align models with human intent, safety, and helpfulness through reinforcement learning workflows - Analyze how models reason through complex chain-of-thought prompts and pinpoint where logic breaks down - Run comparative benchmarks between model outputs using technical taxonomies and quantitative performance metrics

Requirements - BS, MS, or PhD in Computer Science, Artificial Intelligence, Robotics, or a related quantitative field with an ML focus - Hands-on experience building, deploying, or fine-tuning ML models in production environments - Professional-level understanding of neural network architectures such as Transformers, CNNs, and RNNs, plus optimization techniques - Experience with prompt engineering, RLHF, or retrieval-augmented generation workflows - Ability to audit complex model logic, identify training data contamination, and evaluate mathematical proofs behind ML algorithms - Sharp attention to detail for catching hallucinations, biased outputs, and logical failures in AI-generated technical content

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

Benefits and work setup - Remote, task-based work with flexible scheduling - Compensation up to roughly $80 per hour for qualifying studies, with some tasks shorter than a full hour