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Abhishek Gaikwad

Backend Developer | Full Stack Engineer | Java Spring Boot | Python Flask | Microservices | REST API | API Development | Angular React | Docker | GCP AWS | SQL MongoDB | LLM RAG

Davangere

3+ years of work experience

Manomaya AI Systems Private Limited
Apr 20242 yrs 2 mosPresent

Bengaluru

Built and deployed production-grade full stack systems using Angular, React, Spring Boot, and Flask, serving 50-100 active users. Developed DeWiser desktop application (C# / WPF) with real-time hardware monitoring, anomaly detection, and event logging across 50+ devices. Designed and deployed scalable Spring Boot REST APIs (JPA/Hibernate) on GCP Cloud Run using Docker. Built RAG-powered AI chatbot using Flask and GPT-4o-mini with intent classification and knowledge base retrieval. Architected microservices-based systems (ML + API + UI) using Docker for scalable deployments. Followed Git-based development workflows, PR reviews, and API integration testing using Postman. Worked with Docker, MongoDB, SQL, PostgreSQL.
Manomaya AI Systems Private Limited
Sep 20246 mosFeb 2025

Bengaluru

Built and deployed production-grade computer vision systems for real-time airport analytics using YOLOv8, OpenCV, and TensorRT. Improved object detection accuracy from 80% → 96% mAP through model fine-tuning, data augmentation, and transfer learning. Developed Flask-based inference APIs delivering structured JSON outputs (labels, confidence, timestamps) integrated with frontend dashboards. Optimized inference performance using TensorRT (.pt → .engine), reducing latency from 15ms → 3ms (5× improvement) on GPU systems. Containerized ML pipelines using Docker and integrated with full stack applications (React/Angular + Flask APIs) for real-time visualization.
KodNest
Nov 20236 mosApr 2024

Bengaluru, Karnataka, India

upGrad
May 20236 mosOct 2023

Bengaluru, Karnataka, India

Education

GM Institute of Technology

Bachelor of Engineering - BE, Electrical, Electronics and Communications Engineering

GM Institute of Technology

20194 yrs2023

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Abhishek Gaikwad on Tal

Headline

Backend Developer | Full Stack Engineer | Java Spring Boot | Python Flask | Microservices | REST API | API Development | Angular React | Docker | GCP AWS | SQL MongoDB | LLM RAG

About

Full Stack Engineer with 2+ years of experience building scalable backend systems and AI-powered applications. Strong expertise in Java Spring Boot, Microservices, and REST API development, along with frontend experience in Angular and React. Experienced in designing and deploying containerized applications using Docker on GCP Cloud Run. Built production-ready LLM/RAG-based systems including AI chatbots with structured output handling and retrieval pipelines. Also worked on real-time computer vision systems using YOLO and OpenCV. Focused on building high-performance, reliable, and scalable systems end-to-end.

Location

Davangere

Work experience

Full Stack Engineer at Manomaya AI Systems Private Limited, Apr 2024 - Present · 2 yrs 2 mos, Bengaluru, Built and deployed production-grade full stack systems using Angular, React, Spring Boot, and Flask, serving 50-100 active users. Developed DeWiser desktop application (C# / WPF) with real-time hardware monitoring, anomaly detection, and event logging across 50+ devices. Designed and deployed scalable Spring Boot REST APIs (JPA/Hibernate) on GCP Cloud Run using Docker. Built RAG-powered AI chatbot using Flask and GPT-4o-mini with intent classification and knowledge base retrieval. Architected microservices-based systems (ML + API + UI) using Docker for scalable deployments. Followed Git-based development workflows, PR reviews, and API integration testing using Postman. Worked with Docker, MongoDB, SQL, PostgreSQL.

Machine Learning Engineer at Manomaya AI Systems Private Limited, Sep 2024 - Feb 2025 · 6 mos, Bengaluru, Built and deployed production-grade computer vision systems for real-time airport analytics using YOLOv8, OpenCV, and TensorRT. Improved object detection accuracy from 80% → 96% mAP through model fine-tuning, data augmentation, and transfer learning. Developed Flask-based inference APIs delivering structured JSON outputs (labels, confidence, timestamps) integrated with frontend dashboards. Optimized inference performance using TensorRT (.pt → .engine), reducing latency from 15ms → 3ms (5× improvement) on GPU systems. Containerized ML pipelines using Docker and integrated with full stack applications (React/Angular + Flask APIs) for real-time visualization.

Full-stack Developer at KodNest, Nov 2023 - Apr 2024 · 6 mos, Bengaluru, Karnataka, India

Data Analyst at upGrad, May 2023 - Oct 2023 · 6 mos, Bengaluru, Karnataka, India

Education

Bachelor of Engineering - BE, Electrical, Electronics and Communications Engineering, GM Institute of Technology

Abhishek Gaikwad - Full Stack Engineer in Davangere | Tal