AI Engineer/ML Engineer - Senior Developers - AI Training - Dallas, USA

Role overview A paid expert network is recruiting senior AI and machine learning engineers to help train and assess the next generation of large language models. The work is remote and project-based, centering on rigorous technical review, code auditing, and structured feedback rather than ongoing product engineering.

Responsibilities - Evaluate AI-generated technical content on model architectures, loss functions, and backpropagation for correctness - Audit ML code, training loops, and data preprocessing scripts to confirm efficiency and reliability - Contribute high-quality human feedback that supports reinforcement learning from human feedback and model alignment efforts - Examine chain-of-thought reasoning and identify where an AI model's logic fails or diverges - Benchmark model outputs against defined taxonomies and performance criteria

Requirements - Degree (BS, MS, or PhD) in Computer Science, Artificial Intelligence, Robotics, or a quantitative discipline with an ML emphasis - Demonstrated experience building, deploying, or fine-tuning ML models in production - Strong grasp of neural network architectures including Transformers, CNNs, and RNNs, along with optimization methods - Practical experience with prompt engineering, RLHF, or retrieval-augmented generation systems - Capacity to inspect complex model behavior, detect training data contamination, and reason about algorithmic proofs - Meticulous attention to detail in spotting hallucinations, bias, and logical flaws

Nice to have - Deep proficiency in PyTorch or TensorFlow/Keras - Strong Python skills using NumPy, Pandas, Scikit-learn, and the Hugging Face Transformers library - Familiarity with cloud ML platforms like AWS SageMaker or Google Vertex AI, plus tooling such as Weights & Biases and LangChain - Exposure to vector databases such as Pinecone, Milvus, or Weaviate

Benefits and work setup - Fully remote, task-based engagement with flexible hours - Hourly compensation reaching up to around $80 for in-demand tasks; many studies run less than an hour