Headline

QA/QC Trainee focused on AS9100 D compliance and quality assurance.

About

Currently a QA/QC Trainee at System Controls Technology Solutions Private Limited, contributing to quality assurance and control activities for defense and industrial electronics projects. Responsibilities include inspecting electronic components for compliance with engineering standards, supporting Acceptance Test Procedures (ATP), and ensuring adherence to AS9100D Quality Management System standards. Collaborated with teams on projects for BEL Ghaziabad, BEL Hyderabad, and Larsen & Toubro, emphasizing quality in manufacturing and testing processes. Pursuing a Bachelor of Technology (BTech) in Electronics and Communication at Nitte Meenakshi Institute of Technology, with a strong focus on Quality Assurance Analysis and Test Assurance. Committed to driving product excellence through precise inspections and documentation. Dedicated to advancing expertise in quality management systems and contributing to high-standard technological development.

Location

Greater Bengaluru Area

AI stack

claude

gemini

openai

ChatGPT

ChatGPT Images

Microsoft Copilot

Work experience

Quality Assurance & Quality Control (QA/QC) Trainee (NATS) Company at System Controls Technology Solutions Private Limited, Jul 2025 - Jul 2026 · 1 y, Bengaluru, • Perform incoming inspection of electronic and electrical components to ensure compliance with quality standards and engineering specifications. • Conduct Quality Assurance (QA) and Quality Control (QC) activities for defense and industrial electronics projects. • Support Acceptance Test Procedures (ATP) and verification of electronic systems. • Collaborate with cross-functional teams to ensure product quality throughout manufacturing and testing. • Contributed to projects for BEL Ghaziabad, BEL Hyderabad, and Larsen & Toubro (L&T) while adhering to defense quality standards. • Supported the preparation and maintenance of AS9100D Quality Management System documentation for internal and external audits. • Assisted the QA team in ensuring compliance with AS9100D requirements, contributing to the successful completion of the audit and certification.

Intern at CSIR Fourth Paradigm Institute - India, Apr 2025 - Jul 2025 · 4 mos, Bengaluru, Karnataka, India, As part of CSIR-4PI’s prestigious Climate and Environmental Modelling Program, I worked on a multi-phase research initiative to analyze historical climate data and predict future environmental trends using advanced machine learning and deep learning models. My primary focus was on rainfall and temperature forecasting for Indian cities, with case studies on Kanpur and Bangalore, covering data from 1981 to 2024. Developed and trained ML/DL models including Linear Regression, Random Forest, LSTM, and CNN in Python, achieving prediction accuracies as high as 92%, depending on the region and weather parameter. Implemented robust data preprocessing pipelines (scaling, normalization, outlier removal, temporal segmentation), which significantly improved model convergence and accuracy. Designed time-series forecasting workflows using LSTM and CNN architectures, optimized using GPU acceleration, reducing training time while maintaining model generalizability. Conducted comparative analysis between cities, identifying local patterns, seasonal variability, and year-over-year rainfall fluctuations. Worked on hybrid CNN-LSTM models to improve correlation between predicted and actual rainfall, and experimented with reducing training epochs while preserving performance. Proposed a conceptual framework to integrate real-time IoT sensor data (e.g., humidity, pressure, soil moisture) and satellite-based communication to enable dynamic, location-specific forecasting in future applications. Documented all experiments, maintained Git-based version control, and collaborated with climate scientists and engineers to align predictions with ground realities and policy-relevant outcomes. This internship not only deepened my understanding of climate modeling and AI but also strengthened my skills in Python-based data science, signal processing, and system integration – aligning with my broader goal of contributing to intelligent, sustainable, and tech-driven environmental solutions.

Environmental Intern at CSIR 4PI, Apr 2025 - Jul 2025 · 4 mos, Development and deployment of ML/DL models for climate forecasting, data preprocessing, and research collaboration. Developed machine learning (ML) and deep learning (DL) models using Python for climate trend forecasting. Utilized Linear Regression, Random Forest, LSTM, and CNN algorithms. Optimized data preprocessing techniques to improve model performance. Employed GPU-based training methodologies to accelerate model development. Conducted collaborative research on IoT-integrated real-time monitoring systems.

Education

Bachelor of Technology - BTech, Electronics and communication, nitte meenakshi institute of technology

PU, PCMB, Chethana PU College