AI Engineer with 1+ years in Data Analytics & Machine Learning
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Solutions driven Computer Science graduate with foundation in science, robotics, software development, and technology. Expertise in problem solving, analytical thinking, and AI tools. Proven track record of architecting scalable backend systems, full-stack applications, data analytics, and machine learning models to solve complex challenges. Adept at managing end-to-end product lifecycle; from Minimum Viable Products (MVPs) to interactive dashboards that contribute to operational efficiency. Eager to leverage coding abilities, cross-functional task management, and passion for intelligent systems for technical solutions and business impact.
Shiv Nadar University
B.Tech Computer Science & Engineering · Computer Science & Engineering
August 1, 2022 – May 1, 2026
The Mother's International School
CBSE Board 12th
June 1, 2016 – May 1, 2022
The Mother's International School
CBSE Board 10th
June 1, 2016 – May 1, 2022
Nupeak IT Services Pvt. Ltd.
Data Analytics / SAS Intern
May 1, 2025 – July 1, 2025
New Delhi, Delhi, India
Jawaharlal Nehru University (JNU)
Computer Vision Summer Intern
June 1, 2024 – August 1, 2024
New Delhi, Delhi, India
Corporate Infotech Pvt. Ltd. (CIPL)
Web Development Trainee
June 1, 2023 – July 1, 2023
Noida, Uttar Pradesh, India
Face Anti-Spoofing
January 1, 2024 – December 31, 2024
Engineered a custom CNN integrated with Squeeze-and-Excitation attention mechanisms to prioritize facial liveness cues over spatial noise, achieving 98.8% validation accuracy and a 1.0 AUC, verified via Grad-CAM heatmaps. Built a CPU-optimized, real-time computer vision pipeline using OpenCV and Haar Cascades for ROI extraction, implementing data augmentation (RandomCrop) and class weighting to neutralize a 5:1 dataset imbalance.
Stress Detection
January 1, 2024 – December 31, 2024
Architected a high-performance backend system using FastAPI and PyTorch to deploy fine-tuned transformer models, achieving sub-3-second inference latency for real-time, 7-class emotion and sentiment classification. Designed a resource-efficient, CPU-optimized data pipeline integrating NLP heuristics to compute granular 0-100 stress and wellbeing metrics, served seamlessly via a responsive frontend user interface.
Multimodal AI Commentary System
January 1, 2024 – December 31, 2024
Created a real-time, multimodal data processing pipeline utilizing OpenCV and NLP to evaluate and classify live football video events (pass, shoot, corner), increasing the event-match accuracy rate to 76.7%. Trained and optimized a large language model (GPT-2) on 9,207 context-aware match captions from the SoccerNet-v2 dataset, demonstrating proficiency in data engineering and automated content generation.
AI-Powered Ticket Triage
January 1, 2024 – December 31, 2024
Made a scalable, full-stack web application utilizing FastAPI and Streamlit to automate the categorization and intelligent routing of high-volume customer support tickets. Developed a robust backend architecture with a normalized persistence layer (SQLite, SQLAlchemy ORM) enforcing strict API data contracts via Pydantic schemas; integrated a custom NLP engine to compute dynamic confidence scores, optimizing ticket resolution workflows.
Microsoft Generative AI Foundations
Microsoft
June 1, 2026 – Present
IBM Cybersecurity Tools
IBM
June 1, 2026 – Present
INSEAD Blockchain Technologies
INSEAD
June 1, 2026 – Present
DeepLearning.AI ML Specialization
DeepLearning.AI
June 1, 2026 – Present
NPTEL IOT
NPTEL
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects are diverse, covering computer vision, NLP, multimodal AI, and full-stack development, which aligns well with the broad scope of an AI Engineer role. The internships, while varied (Computer Vision, Web Development, Data Analytics), show a willingness to explore different technical areas. The certifications in Generative AI, ML Specialization, and IoT indicate a proactive approach to learning and staying current with industry trends, suggesting a good cultural fit for a dynamic and innovative environment.
Soft Skills & Operational Fit
The candidate's project descriptions highlight problem-solving, analytical thinking, and an end-to-end product development mindset. The 'Data Analytics / SAS Intern' role shows collaboration with stakeholders and validation of technical approaches, indicating good operational fit. The academic projects demonstrate initiative and the ability to manage complex challenges independently.