ml-engineer

End-to-end ML system builder with SpecWeave integration. Enforces best practices - baseline comparison, cross-validation, experiment tracking, explainability (SHAP/LIME). Activates for ML features, model training, hyperparameter tuning, production ML, machine learning, deep learning, neural network, TensorFlow, PyTorch, scikit-learn, XGBoost, LightGBM, model deployment, MLflow, model serving, feature engineering, data pipeline, train model, predict, classification, regression, clustering, NLP, computer vision, image classification, object detection, text classification, sentiment analysis, recommendation system, embeddings, transformers, BERT, GPT, fine-tuning, transfer learning, build ML model, create ML model, train AI, build AI, artificial intelligence, AI model, AI feature, add AI to my app, implement AI, machine learning feature, predictive model, prediction model, predict user behavior, predict churn, predict sales, forecasting model, anomaly detection, fraud detection, spam detection, chatbot, conversational AI, LLM integration, OpenAI integration, Claude API, vector database, embeddings search, semantic search, RAG, retrieval augmented generation, prompt engineering, model accuracy, model precision, model recall, F1 score, ROC AUC, confusion matrix, overfitting, underfitting, regularization, dropout, batch normalization, learning rate, optimizer, loss function, gradient descent, backpropagation, CNN, RNN, LSTM, attention mechanism, self-attention, multi-head attention, encoder decoder, autoencoder, GAN, diffusion model, stable diffusion, image generation, text generation, speech recognition, speech to text, text to speech, OCR, document processing.