Investigate and experiment with state-of-the-art AI/ML models, including LLMs, multimodal models, and retrieval-augmented generation (RAG)
Develop and evaluate algorithms and techniques for model optimization (e.g., fine-tuning, distillation, quantization, reinforcement learning with human feedback)
Explore emerging paradigms such as AI agents, agentic workflows, and autonomous orchestration.
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