AI/ML Architect

- Design, build, and train end-to-end machine learning models across NLP, predictive analytics, classification, and computer vision use cases - Experiment with algorithms, optimize hyperparameters, and evaluate model performance - Collect, process, and prepare structured and unstructured datasets for model training and validation - Implement feature engineering, data augmentation, and data quality controls - Develop APIs, services, or microservices to integrate models into production platforms - Deploy, monitor, and manage models using MLOps tooling, automation, and versioning practices - Analyze performance metrics (accuracy, precision, recall, F1-score) and optimize models for scalability and efficiency - Collaborate with product teams, engineers, and data scientists to translate business requirements into technical solutions - Document architectures, workflows, and methodologies to ensure reproducibility and maintainability - Stay current on emerging AI technologies including generative models, reinforcement learning, and transformer-based architectures