AI Engineer/ML Engineer - Senior Developers - AI Training - El Paso, US

Role overview This opportunity invites senior AI and Machine Learning Engineers into an expert contributor network focused on training and evaluating next-generation large language models. Participants take on paid technical assignments that draw on production ML experience, with task lengths ranging from short audits to sessions lasting up to one hour. The work is fully remote and schedule-flexible, allowing experienced engineers to contribute alongside other commitments.

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 routines, for correctness and efficiency - Deliver high-quality human feedback that powers RLHF pipelines and improves model alignment, safety, and helpfulness - Critically assess chain-of-thought reasoning and identify exactly where model logic breaks down - Run comparative benchmarks across model outputs using defined technical taxonomies and performance metrics

Requirements - Bachelor's, Master's, or PhD in Computer Science, Artificial Intelligence, Robotics, or a related quantitative field with a machine learning focus - Production experience building, deploying, or fine-tuning machine learning models - Professional-level understanding of neural network architectures such as Transformers, CNNs, and RNNs, along with modern optimization techniques - Hands-on experience with prompt engineering, RLHF, or retrieval-augmented generation workflows - Ability to audit complex model logic, identify training data contamination, and assess 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, including NumPy, Pandas, and Scikit-learn, plus experience with Hugging Face Transformers - Familiarity with AWS SageMaker, Google Cloud Vertex AI, Weights & Biases, or LangChain - Experience with vector databases such as Pinecone, Milvus, or Weaviate for RAG evaluation

Benefits and work setup - Hourly compensation reaching up to $80 per hour depending on the researcher and task - Fully remote with flexible hours and the ability to work from home - Onboarding begins after a short 10-15 minute skills assessment; participants choose tasks that fit their availability