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Niyaz Nurbhasha
Mid-level Machine Learning Engineer specializing in computer vision and LLM pipelines
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About
ML/LLM engineer who built production systems to speed up artist content-creation workflows, including a fine-tuned image captioning model paired with a RAG layer over image embeddings/captions to improve consistency across changing domains. Experienced orchestrating multi-tool agents with LangChain/LangGraph (planning + critic/reflection) and setting up practical monitoring (caption rejection rate) plus evaluation sets for tool-calling accuracy, output quality, and latency.
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Key Strengths
- Built and deployed production image-captioning system augmented with RAG for consistent tagging across domains
- Designed monitoring signal (caption rejection rate) to detect model drift/inaccuracy and trigger retraining
- Hands-on orchestration of multi-tool LLM agents using LangChain/LangGraph (planning, tool selection, reflection/critic loop)
- Structured agent evaluation approach across task success, tool correctness, latency, safety/compliance, and hallucinations
- Effective collaboration with product and artist teams using iterative demos, feedback loops, and expectation-setting
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