AI Engineer with less than a year in deep learning, NLP, and large-scale ML systems development.
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As an AI Developer Intern, Suyash Gupta has processed 100,000+ data points for deep learning, optimized ML models reducing memory consumption by 18%, and scaled NLP infrastructure to support 500+ concurrent users. His projects include developing a real-time voice cloning and TTS system, a RAG-based chatbot (GovGuide AI), and an academic placement portal. With strong technical skills in Python, PyTorch, LangChain, and machine learning, Suyash is poised to contribute effectively in AI and data science roles.
IIT Madras
BS Degree · Data Science and Applications
August 1, 2024 – June 30, 2028
Rajiv Gandhi Institute of Petroleum Technology
B Tech · Computer Science and Engineering
August 1, 2023 – June 30, 2027
CBSE Board
Senior Secondary
June 1, 2022 – May 31, 2023
CBSE Board
Secondary
June 1, 2020 – May 31, 2021
Prodigal AI
AI Developer Intern
June 1, 2025 – August 15, 2025
India
Placement Portal Application
March 1, 2026 – March 1, 2026
App Dev Academic Project Tech Stack: Python, Flask, SQLite, Jinja2, HTML/CSS, Bootstrap Built a role-based campus recruitment portal for secure workflows between admins, companies, and students. Engineered dynamic Flask/Jinja2 dashboards to manage company approvals, placement drives, and real-time application tracking. Designed an SQLite database to manage user profiles, maintain historical records, and prevent duplicate submissions.
Real-Time Voice Cloning and TTS
March 1, 2025 – March 1, 2025
Developed a deep learning-based TTS system with voice cloning capabilities Tech Stack: Python, PyTorch, NumPy, Librosa, Tacotron, WaveRNN, Speaker Embeddings Engineered a low-latency TTS pipeline capable of cloning voices from short reference audio (<5 sec) Implemented local-only inference to ensure privacy, integrating spectrogram generation and vocoding for real-time synthesis.
View ProjectGovGuide AI (MyScheme)
March 1, 2025 – June 1, 2025
Developed a RAG-based chatbot to help users discover government schemes from the MyScheme portal. Tech Stack: Python, Selenium, BeautifulSoup, LangChain, FAISS, LLMs, and Streamlit Built a FAISS vector database by automating data extraction with Selenium and BeautifulSoup. Architected a RAG pipeline to ground LLM responses and minimize hallucinations. Deployed a Streamlit interface to enable conversational querying of government data.
View ProjectIIT Madras: Achieved 'Topper' status in all courses IIT Madras.
IIT Madras
June 1, 2026 – Present
GATE 2026: Secured AIR 2519 in CS (Score: 625) and AIR 4730 in DA (Score: 434)
Unknown
March 1, 2026 – Present
Visa CodeSignal Assessment: Achieved a perfect score of 600/600
CodeSignal
December 1, 2025 – Present
Qualified: JEE ADVANCED (Top 1% students )
Unknown
January 1, 2023 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from deep learning-based TTS to RAG chatbots and a full-stack web application, indicates a broad interest in different areas of computer science and AI. This adaptability and willingness to explore various domains suggest a good cultural fit for a dynamic AI engineering role that often requires tackling diverse challenges. The academic background from multiple reputable institutions (RGIPT, IIT Madras) and consistent high performance further highlight a strong work ethic and commitment to excellence, which are valuable cultural attributes. The personal projects demonstrate initiative and self-driven learning, aligning well with an innovative and growth-oriented team.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills through project implementations and a proactive approach to learning new technologies. The internship experience at Prodigal AI suggests an ability to contribute to production-level tasks and work within a team, processing large datasets and optimizing models. The psychometric test score indicates a reasonable capacity for logical reasoning and work attitude, though there might be areas for improvement in stress handling or team collaboration given it's not a top score. The candidate's project descriptions are clear and concise, indicating good communication skills in a technical context.