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AI Engineer with less than a year in Machine Learning & NLP.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI & Machine Learning Engineer with hands-on experience in Machine Learning, NLP, Generative AI, RAG pipelines, and Computer Vision. Skilled in developing AI-powered applications using Python, TensorFlow, and LLM-based architectures. Strong foundation in data analysis, deep learning, and building end-to-end intelligent systems.
Bansal Institute of Engineering and Technology
B.Tech · Artificial Intelligence & Machine Learning
August 1, 2022 – June 30, 2026
National Institute of Technology (NIT), Meghalaya
Polyp Segmentation using Advanced Focus U-Net
July 1, 2025 – August 31, 2025
India
HCL Technologies
Hotel Management System
September 1, 2024 – November 30, 2024
India
Face Pay – Facial Recognition Payment System
June 1, 2026 – Present
Developed facial recognition-based authentication system for secure transactions. Implemented real-time face detection and matching using OpenCV algorithms.
Movie Recommendation System
June 1, 2026 – Present
Built recommendation engine using similarity-based filtering techniques. Processed movie datasets to generate personalized recommendations for users.
Doctor AI – GenAI Medical Assistant
June 1, 2026 – Present
Developed RAG-based medical assistant using LLMs and vector search for medical query answering. Integrated LangChain workflow with semantic retrieval to improve response accuracy.
Java Programming
Great Learning
June 1, 2026 – Present
Python Development
HCL Technologies
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity (GenAI medical assistant, facial recognition, movie recommendations) and internship experiences (deep learning for medical imaging, hotel management system) suggest a broad interest in applying AI across different domains. This indicates a potential for adaptability and a willingness to explore various challenges, which can be a good cultural fit for dynamic AI teams. The focus on practical application aligns with a results-oriented culture.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on diverse AI applications, suggesting adaptability. The internship experience, though limited, shows exposure to structured development environments. However, without specific behavioral assessment data, it is difficult to fully assess soft skills like teamwork, problem-solving under pressure, or communication in a collaborative setting.