Ronak Bhattad

Software Engineer

Hyderabad, Telangana, India4 yrs 9 mos experience

Highly Stable

Key Highlights

Expert in AWS and finance automation solutions.
Proficient in building scalable web applications.
Strong background in machine learning and neural networks.

Stackforce AI infers this person is a Fintech-focused Software Developer with expertise in cloud technologies and machine learning.

Contact

ronakbhattad18@gmail.com LinkedIn

Skills

Core Skills

AwsWeb DevelopmentNeural NetworksVerilog

Other Skills

React.jsCI/CDREST APIsObject DetectionData StructuresAlgorithmsMachine LearningSpring FrameworkC++PythonMatlabJestCypress.ioJUnitGit

About

Currently a Software Developer at Amazon, part of the finance automation team. I completed my under-graduation from BITS Pilani, Pilani Campus. I am particularly interested in the fields of Cloud Computing, Distributed Systems and Machine Learning.

Experience

4 yrs 9 mos

Total Experience

4 yrs 6 mos

Average Tenure

3 mos

Current Experience

Microsoft

Software Engineer

Feb 2026 – Present · 3 mos · On-site

Amazon

3 roles

SDE2

Promoted

Nov 2023 – Feb 2026 · 2 yrs 3 mos

SDE

Jul 2021 – Oct 2023 · 2 yrs 3 mos

SDE

Jan 2021 – Jun 2021 · 5 mos

Worked in the Finance Automation department building an AWS Web Application
· Leveraged AWS technologies including CDK, Cloudfront to implement a CI/CD Pipeline.
· Implemented custom authentication and authorisation to secure REST API for S3, AppConfig and AWS Lambda.
· Built a dynamic UI with ReactJS, using Jest for Unit testing and Cypress for automated Integration testing.

AWSWeb DevelopmentReact.jsCI/CDREST APIs

Csir-ceeri

Research Intern

May 2019 – Aug 2019 · 3 mos · Pilani, Rajasthan

· Researched under Dr. Jai Gopal Pandey, assisting in building a Convolutional Neural Network for the purpose of Object Detection and localization on a Xilinx FPGA in Verilog HDL.
· Successfully implemented the network based off of TinyYOLO v2 architecture and benchmarked on Microsoft's COCO dataset achieving an accuracy of 63.7% at 16.79 FPS.

VerilogNeural NetworksObject Detection