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AI Engineer with less than a year in Full-Stack LLM Applications & Machine Learning
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Final-year Computer Engineering student at Nirma University specializing in AI Engineering, full-stack LLM applications, RAG systems, and applied machine learning. Experienced in building end-to-end AI products involving document ingestion, semantic search, vector databases, LLM orchestration, backend workflows, and user-facing AI interfaces using Python, LangChain, modern LLM APIs, and ML/DL frameworks. Runner-up at the National Level MINED Hackation for an automated podcast generation system.
Nirma University
Bachelor of Engineering · Computer Science and Engineering
August 1, 2022 – June 30, 2026
Asian International Private School
Higher Secondary School Certificate (CBSE)
June 1, 2020 – May 31, 2022
E2M Solutions
AI Intern
January 1, 2026 – Present
India
Sinuvera Technologies
AI Research Intern
May 1, 2025 – June 1, 2025
India
Virtual Psychiatrist (Mental Health Assistant)
June 30, 2026 – June 30, 2026
Designed a Virtual Psychiatrist combining sentiment analysis, attention-based emotion detection, and LLM-powered conversation handling to address student stress and mental wellness support through natural conversational interaction using text-to-speech for a human-like counselling experience. Enabled real-time emotion tracking across conversation turns, allowing the chatbot to actively respond with supportive dialogue transforming negative affect into a milder or positive emotional outcome over multiple turns. Developed Emotion Classification model with 95% evaluation accuracy and consistent therapy based Counselling.
View ProjectAutomated Podcast Generation
June 30, 2026 – June 30, 2026
Built a system that converts Academic or research papers/documents into long-form podcast dialogues using LLM-generated multi-speaker conversation. Enabled customization of host count, tone, audience type, and session style for tailored content generation. Used Google TTS and ElevenLabs to generate realistic and diverse voice profiles for different characters within the podcast, simulating multi-host discussion naturally.
View ProjectNavIC-based Distress Signal Identification & Emergency Transmission System
June 30, 2026 – June 30, 2026
Research and prototyping of a system for distress audio signal detection using ML-based classifier models. Designing workflows for transmitting real-time location coordinates (Latitude/Longitude) via NavIC + GSAT transceivers. Objective: enable rapid emergency alert relays for disaster-response, civilian safety, and remote-area assistance.
Deep Learning Specialization
DeepLearning.AI
June 30, 2026 – Present
MINED Hackation
Unknown
June 30, 2026 – Present
Cultural Fit Analysis
The candidate demonstrates a strong cultural fit for an AI Engineer role through a clear passion for AI/ML, evidenced by specialized education, diverse academic and internship projects, and relevant certifications. The projects showcase innovation and a practical application of AI to solve real-world problems (mental health, content generation, emergency systems). Participation in hackathons and extracurricular activities suggests a collaborative spirit and a well-rounded individual. The experience with various LLMs and tools indicates adaptability and a willingness to explore different technologies, which is crucial in a rapidly evolving AI landscape.
Soft Skills & Operational Fit
The candidate's project descriptions and experience indicate strong problem-solving abilities, a proactive approach to learning new technologies, and an ability to work in team settings (evidenced by hackathon participation and client discussions). The detailed descriptions suggest good communication skills in conveying technical work. The internship experience at E2M Solutions highlights operational fit through participation in client-facing product discussions and aligning AI product workflows with client expectations.