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AI Engineer with less than a year in machine learning systems, data processing, and Python.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Software Engineer specializing in Python, machine learning systems, computer vision, data processing, and AI applications, focused on building intelligent systems, foundation model applications, semantic search platforms, and scalable ML inference solutions.
Lovely Professional University
B.Tech · Computer Science
August 1, 2022 – June 30, 2026
FlickDone
Data Engineer Intern
June 1, 2025 – August 31, 2025
India
AI Product Recommender System
June 1, 2026 – Present
Built LLM-based semantic search and retrieval system using FastAPI, embeddings, RAG pipelines, and OpenAI API for context-aware recommendations, improving query relevance and reducing API latency by 35%.
View ProjectSmart Traffic AI Surveillance System
June 1, 2026 – Present
Built computer vision system using Python, YOLO, OpenCV, FastAPI, OCR, and FaceNet for real-time object detection, tracking, and monitoring. Deployed ML inference pipelines on AWS for scalable processing.
View ProjectRails TODO Application
June 1, 2026 – Present
Designed RESTful backend services using MVC architecture, optimizing database schema and query performance, improving system efficiency and API response time by 20%.
View ProjectGenerative AI
DeepLearning.AI
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from LLM-based systems to computer vision and general backend development, indicates a broad interest in various technical domains. The involvement in founding a technical organization (CAT AI) and participating in hackathons suggests a proactive and innovative mindset, which could be a good cultural fit for a dynamic AI engineering team. The focus on performance optimization and scalable solutions aligns with industry best practices. However, the candidate's experience level is '0', indicating a fresh graduate, which might require more mentorship and integration into a senior team's workflow.
Soft Skills & Operational Fit
The candidate demonstrates initiative through personal projects and extracurricular activities (founding CAT AI, Hackfest win). The descriptions of project impacts (e.g., 'improving query relevance and reducing API latency by 35%') suggest a results-oriented approach. The internship experience indicates an ability to work in a professional setting and contribute to operational improvements (e.g., 'resolved CI/CD pipeline failures'). However, without direct interview data, a comprehensive assessment of soft skills like teamwork, leadership, and adaptability is limited.