AI Developer focused on architecting intelligent systems at scale — integrating LLMs, transformer-based architectures, and hybrid learning frameworks across distributed environments. Experienced in building modular pipelines leveraging vector databases, GPU-accelerated training, and on-device inference. Skilled in prompt engineering, fine-tuning foundation models, and optimizing attention mechanisms for real-time, low-latency applications. I work across MLOps stacks (Docker, Kubernetes, MLflow), deploy through CI/CD on cloud-native infrastructure, and track model drift with active monitoring. Passionate about pushing the limits of machine intelligence, from zero-shot learning to agent-based systems. My goal isn’t just automation — it’s autonomy, at scale.
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