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AI Engineer with less than a year in Machine Learning & GenAI.
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Kushagra Jain is an aspiring AI Engineer with 9 months of hands-on experience in AI/ML development and research. He has designed and deployed robust AI/ML solutions, including async API gateways for LLM backends, RAG systems, and multi-agent pipelines. His expertise spans prompt engineering, LLM fine-tuning, and developing real-time voice-based AI assistants, demonstrating a strong commitment to building scalable and efficient AI products.
D.Y. Patil College of Engineering
B.Tech · Computer Science and Engineering
August 1, 2022 – June 30, 2026
ScotAI
AI/ML Developer Intern
January 1, 2026 – June 1, 2026
Pune, Maharashtra, India
Responsible AI Labs
AI/ML Intern
September 1, 2025 – November 1, 2025
India
Alvocate - AI Powered Legal Assistant
June 1, 2025 – July 1, 2025
Built an AI-powered legal assistant using LangChain, Groq LLMs, and Streamlit, enabling users to ask natural language legal queries and receive accurate, context-aware answers in real time. Implemented a Retrieval-Augmented Generation (RAG) pipeline with semantic search and vector databases to fetch relevant legal documents and enhance LLM response precision.
View ProjectMedimate - AI Doctor with Voice and Vision
March 1, 2025 – April 1, 2025
Built a real-time AI doctor assistant combining voice and vision for diagnostics. Integrated LLaMA 3 Vision, Whisper, and Groq with voice synthesis for interactive responses.
View ProjectKrishi Nirogyam – Plant Disease Detection System
August 1, 2024 – September 1, 2024
Developed a Convolutional Neural Network (CNN) model to detect plant diseases across 38 categories using image processing and data augmentation. Built a high-accuracy CNN-based plant disease detection system using preprocessing, augmentation, and deep learning, enabling scalable early detection for precision agriculture.
View ProjectDSA in C++
Learnyard
June 1, 2026 – Present
Fundamentals of Deep Learning
NVIDIA
March 29, 2025 – Present
MERN Stack Development
100xDevs
December 3, 2024 – Present
Cultural Fit Analysis
The candidate's involvement in diverse personal projects and internships, including 'Responsible AI Labs', suggests an interest in impactful and ethical AI development. The breadth of skills and technologies listed indicates a willingness to learn and adapt, which aligns well with dynamic and innovative team environments. The focus on end-to-end product development and scalable solutions demonstrates a practical mindset valuable for collaborative engineering cultures.
Soft Skills & Operational Fit
The candidate's project descriptions and internship experiences indicate a proactive and results-oriented approach. The focus on transforming GenAI research into scalable products suggests an operational fit for roles requiring practical implementation and deployment. The diversity of projects (legal, medical, agriculture) implies adaptability and a broad interest in applying AI solutions.