AI Engineer with less than a year in Python, Data Analytics & AWS
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Assessing your cultural and operational fit
Computer Science graduate with hands-on experience in Python, data analytics, machine learning, and cloud infrastructure. Proficient in building ETL pipelines, deploying applications on AWS (EC2, S3, IAM, VPC), and creating interactive dashboards. Experienced in NLP-based systems, computer vision, and IoT-integrated data pipelines. Seeking cloud infrastructure or data engineering roles to apply Python, AWS, and ML expertise in a dynamic organization.
College of Engineering Muttathara
Bachelor of Technology · Computer Science and Engineering
August 1, 2022 – June 30, 2026
AI-Driven Dry Eye Detection & IoT Mitigation
May 1, 2026 – June 1, 2026
Developed a real-time computer vision diagnostic pipeline using Python, OpenCV, and dlib with a custom blink-rate ML classifier, attaining 94% detection accuracy across 500+ validated test frames at 30+ FPS. Engineered a low-latency edge-to-cloud IoT data pipeline transmitting JSON biometric telemetry from an ESP32 microcontroller to Firebase Realtime Database with under 200ms end-to-end latency. Automated clinical-threshold alerting via a closed-loop embedded control system (PySerial + ESP32), capturing 100+ hours of continuous ambient sensor data and triggering corrective responses with 0 false negatives.
View ProjectAI Document Chatbot
April 1, 2026 – June 1, 2026
Architected and deployed a lightweight RAG pipeline on AWS EC2 to process 100+ page PDF documents with chunk-level TF-IDF retrieval, reducing manual document search effort by 70% and improving query response relevance by ~80%. Provisioned AWS S3 for cloud document storage with IAM role-based access control, enabling secure multi-user file uploads and eliminating unauthorised access across all test sessions. Integrated Groq LLM API for sub-second contextual question answering and deployed the full Streamlit application on AWS EC2, achieving public cloud accessibility with 99% uptime across testing.
View ProjectCustomer Behavior Analysis
January 1, 2026 – June 1, 2026
Designed and deployed an end-to-end ETL pipeline to ingest, validate, and transform 50,000+ transaction records using Python (Pandas, NumPy), reducing data inconsistencies by 98% and cutting preprocessing time by 40%. Optimised 15+ complex SQL queries with joins, window functions, and aggregations on a PostgreSQL relational database, decreasing average query execution time by 35% and enabling real-time KPI tracking. Delivered 3 interactive Power BI dashboards with drill-through filters, DAX measures, and trend visualisations, eliminating 60% of manual reporting effort and supporting data-driven decision-making for 5+ stakeholders.
View ProjectGoogle Data Analytics Professional Certificate (v.3)
June 1, 2026 – Present
Data Analysis with Python
IBM
June 1, 2026 – Present
GenAI Powered Data Analytics
TATA
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a strong interest in AI, data analytics, and IoT, which aligns well with an AI Engineer role. The diversity of projects (ETL, RAG chatbot, computer vision/IoT) shows a broad technical curiosity and willingness to explore different domains. However, all experience is academic, which might require mentorship to adapt to a corporate environment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on complex, multi-faceted problems, suggesting good problem-solving skills. The focus on end-to-end solutions and deployment implies a results-oriented approach. However, without direct experience or psychometric test results, it's difficult to assess collaboration, stress handling, or communication in a team setting.