Headline

Software Engineer @ Ecolink Solutions | Artificial Intelligence (AI)

About

As a Software Engineer at Ecolink Solutions, I contribute to developing advanced applications and data engineering pipelines. My professional journey includes a prior role as an R&D Associate at Doodil2R IT Solutions, where I built and deployed real-time computer vision pipelines for industrial monitoring. This involved implementing object detection and multi-object tracking systems, optimizing deep learning models for edge deployment on NVIDIA Jetson ORIN Nano using ONNX and TensorRT, and addressing latency bottlenecks through end-to-end performance profiling. My educational foundation in Mathematics (B.Sc. Research, Shiv Nadar University) strengthens my ability to approach technical challenges with first-principles reasoning. Certified in Machine Learning (Stanford, Coursera) and Deep Learning (DeepLearning.AI, Coursera), I am passionate about crafting production-ready, high-performance systems that integrate computer vision, data engineering, and machine learning.

Location

Coimbatore

AI stack

claude code

gemini

langchain

notion

openai

huggingface

Work experience

Software Engineer at Ecolink Solutions, May 2026 - Present · 4 mos, Coimbatore, Tamil Nadu, India

Research And Development Associate at Doodil2R IT Solutions, Nov 2025 - May 2026 · 7 mos, Coimbatore, Tamil Nadu, India, Built and deployed real-time computer vision pipelines for industrial monitoring, including object detection and multi-object tracking systems processing live video feeds on production hardware. Optimized deep learning models for edge deployment on NVIDIA Jetson ORIN Nano using ONNX and TensorRT, achieving low-latency, high-throughput inference through FP16/INT8 quantization. Conducted end-to-end performance profiling and pipeline optimization — diagnosed latency bottlenecks, improved throughput stability, and ensured reliable runtime performance in deployed systems. Designed automated industrial monitoring systems integrating computer vision with real-time alerting mechanisms, reducing manual oversight requirements for continuous operations. Developed an ESP32-based indoor localization system using RSSI signal data, applying ML regression models to predict spatial positioning — engineering features around signal noise, multipath interference, and environmental variability across multiple access points. Worked across the full hardware-software stack, from configuring ESP32 module networks and collecting RSSI training data to building and evaluating ML models for position estimation in RF-challenging indoor environments

Software Development Intern at Infognana (IG) Solutions, Jul 2023 - Aug 2023 · 2 mos, Coimbatore, Tamil Nadu, India, Built a web scraping and analytics pipeline using Python (Flask, Selenium, BeautifulSoup) to extract Google search ranking data for targeted keyword sets, delivering structured SEO insights to clients. Processed and delivered website ranking analytics in structured CSV format, enabling data-driven decision-making for client SEO strategies.

Education

Bachelor of Science - BS, Mathematics, Shiv Nadar University

Higher secondary education, Vidhya Niketan School - India

Public links

github: https://github.com/lakshminarayanan22