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AI Engineer with less than a year in Machine Learning, Deep Learning, and RAG architectures.
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AI enthusiast and a Bachelors of Technology student specializing in Artificial Intelligence. Proven ability to design, develop, and deploy AI systems and machine learning models for real-world applications, achieving high accuracy and efficiency. Experienced in various AI domains including computer vision, natural language processing, and predictive analytics, leveraging frameworks like TensorFlow, PyTorch, and FastAPI.
Aligarh Muslim University
Bachelors of Technology · Artificial Intelligence
August 1, 2021 – June 30, 2025
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Driver Drowsiness Detection
June 24, 2026 – Present
Built a high-performance FastAPI backend with PostgreSQL, implementing a multi-stage auditory alert system and seamless cloud deployment via Render and Vercel. Engineered a real-time, privacy-first driver safety monitor using MediaPipe and React, achieving sub-100ms face landmarker tracking directly in the browser. Integrated Cohere agents to generate personalized safety advice via an event-driven JSON pipeline
View ProjectAI Triage and Support Platform (Agentic RAG)
June 24, 2026 – Present
Accomplished 92% accuracy in automated customer service triage as measured by a 12-case adversarial evaluation suite, by engineering an agentic RAG pipeline that grounds LLM responses in real-time policy data. Achieved 100% downstream reliability for CRM integration as measured by zero schema validation errors, by implementing Pydantic-enforced structured outputs and a self-correction layer for model hallucinations.
View ProjectPhishing URL Detection
June 24, 2026 – Present
Developed using Flask, Scikit-learn, Pickle, and Python to classify URLs as phishing or safe based on 30 custom-extracted features. Demonstrated phishing detection on 50+ test URLs with 30 handcrafted features, achieving over 95% prediction consistency using a pre-trained Gradient Boosting model
View ProjectCultural Fit Analysis
The candidate's portfolio shows a strong interest in practical applications of AI, including safety, customer support, and medical domains. This aligns well with roles that require innovative problem-solving and a focus on real-world impact. The breadth of technologies and project types suggests a curious and adaptable individual, which is beneficial for dynamic team environments. However, the experience is primarily academic and internship-based, which might require mentorship in a fast-paced industry setting.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a results-oriented approach, focusing on metrics like accuracy and latency. The diversity of projects suggests adaptability and a willingness to tackle different problem domains. However, without direct interview data, it's difficult to assess collaboration style, problem-solving under pressure, or communication in a team setting.