Basic Qualifications: Experience developing AI solutions using LLMs, Agentic AI, CNNs, LSTMs, unsupervised learning, reinforcement learning, statistical modeling, AIML frameworks (PyTorch, Keras, Scikit-learn, etc), MLOps pipelines, Cloud services, ETL, training, fine-tuning, evaluation of AI solution, services, containers and container orchestration . Apply machine learning algorithms to large sets of structured and unstructured data to solve a broad range of problems that include applications in pattern recognition, target detection and tracking, decision support systems, and robotic systems.