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AI Engineer with 1+ years in Machine Learning and LLMs.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Aspiring AI/ML Engineer with 10 months of hands-on internship experience in Machine Learning, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI. Driven by a deep curiosity to understand how technologies work internally and apply that knowledge to solve real-world problems. Passionate about learning new technologies, building AI-powered applications, and continuously growing as an AI professional.
Galgotias University
Bachelor of Technology · Computer Science (AI/ML)
August 1, 2022 – June 30, 2026
ShelfEx
AIML Engineer Intern
July 1, 2025 – June 30, 2026
India
Video RAG with Voice Agent
May 1, 2026 – June 30, 2026
Built a multimodal Video RAG platform that enables users to interact with YouTube videos through both text and voice, generating summaries, study notes, and key takeaways from video content. Developed a voice-enabled AI assistant capable of understanding natural language queries and answering context-aware questions based on the video's visual and textual information. Implemented an end-to-end pipeline using frame extraction, vision-language models, embeddings, and vector search to retrieve relevant video segments and generate accurate responses. Integrated conversational memory and voice interaction capabilities to support natural multi-turn conversations and seamless exploration of video content.
Text-to-SQL RAG Chatbot for Retail Intelligence
January 1, 2026 – June 30, 2026
Built an AI-powered Text-to-SQL system that converts natural language business questions into PostgreSQL queries, enabling conversational access to retail analytics data. Implemented schema-aware query generation using Chain of Thought and Few-shot prompting to improve SQL accuracy and reduce invalid query generation. Developed a multi-layer validation framework incorporating schema validation, semantic query verification, automated self-correction on execution errors, and post-execution sanity checks to improve reliability and reduce hallucinations. Engineered session memory, prompt caching, and data dictionary grounding to support multi-turn conversations, reduce operational costs, and enhance schema-aware SQL generation.
Cultural Fit Analysis
The candidate's involvement in a student-led community and CTF challenges suggests a collaborative and growth-oriented mindset. The diversity of projects (Video RAG, Text-to-SQL, Face Verification) indicates adaptability and a broad interest in AI applications. However, with only one internship and no extensive team project experience, the cultural fit for a senior role requiring significant team leadership and mentorship would need further validation.
Soft Skills & Operational Fit
The candidate demonstrates strong initiative and a proactive learning attitude through co-founding a community and participating in CTF challenges. The project descriptions indicate an ability to work on complex, multi-faceted problems. However, with limited professional experience, the operational fit in a senior role would require further assessment of leadership, project management, and collaboration skills in a team setting.