AI Engineer with 1+ years in Agentic AI, Natural Language Processing (NLP), and Fine-Tuning.
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Results-driven AI ML Engineer with 2 years of experience specializing in Agentic AI, Natural Language Processing (NLP), and Fine-Tuning. Proven track record in building Retrieval-Augmented Generation (RAG) systems and orchestrating goal-based agents for complex data analysis. Expert in Parameter-Efficient Fine-Tuning (PEFT) for Vision-Language Models and developing multimodal systems. Focused on architecting emotionally aware AI systems and high-performance memory graphs for production-scale applications.
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B.E. in Electronics and Communication Engineering · Electronics and Communication Engineering
August 1, 2021 – June 30, 2024
Unknown
Diploma in Electronics and Electrical Engineering · Electronics and Electrical Engineering
August 1, 2018 – June 30, 2021
SetNext Technologies Pvt Ltd
AI ML Engineer
September 1, 2024 – Present
India
Incubation cell at IIT Madras XYMA Analytics Pvt Ltd
Computer Vision Intern
January 1, 2024 – February 29, 2024
India
Cultural Fit Analysis
The candidate's experience with diverse AI/ML projects, including Agentic AI, RAG, LLM fine-tuning, multimodal systems, and edge AI, suggests adaptability and a broad interest in the AI domain. Their current role as an AI ML Engineer aligns well with the target role of an AI Engineer, indicating a strong cultural fit for an AI-focused team. The breadth of technical skills listed (LLMs, RAG, PEFT, PyTorch, TensorFlow, Docker, Kubernetes, AWS SageMaker) further supports their potential to integrate into a dynamic AI engineering environment.
Soft Skills & Operational Fit
The candidate's resume indicates a results-driven approach, evidenced by their focus on deploying Agentic AI systems and optimizing algorithms for real-time monitoring. Their experience in leading fine-tuning efforts suggests initiative and project ownership. The descriptions are clear, implying good communication skills in a professional context.