Headline

SDE-2 @HingeHealth || ex-ML Intern @Samsung || ex-ML Intern @IISc || Machine Learning || Databricks certified

About

I pursued EEE from BMS College of Engineering, Bangalore. I worked on multiple ML projects in collaboration with Dassault Systèmes and Samsung PRISM. I also completed an internship with a start-up, where I worked with a tech stack that included OpenCV, NLP, and Flask. At Hinge Health, I worked on projects involving AWS at the architectural level, deploying services on ECS and creating workflows using CloudFormation Templates (CFT). Currently, I am part of the Growth team, where I facilitate data for the marketing teams using Python and Databricks.

Location

Bengaluru

AI stack

antigravity

codex

claudecode

Work experience

Software Engineer 2 at Hinge Health, Mar 2026 - Present · 6 mos, Bengaluru

Software Engineer-1 at Hinge Health, Jul 2024 - Mar 2026 · 1 yr 9 mos, Bengaluru, Karnataka, India, Designed and optimized PySpark pipelines to transform large-scale event data from raw to curated layers, enabling real-time marketing automation via Iterable. Replaced a 10-minute batch job (~$600/month cost) with an optimized PySpark streaming solution, reducing latency by 90% and saving 60% in monthly costs. Orchestrated batch and streaming ETL workflows using Apache Airflow, with SLA tracking, retries, and dependency management. Wrote unit tests using Pytest, ensuring high test coverage and reliability for core video processing and batch tracking components.

Software Engineer Intern at Hinge Health, Aug 2023 - Jun 2024 · 11 mos, Bangalore, Developed and maintained a FastAPI-based computer vision microservice that processed 10,000+ exercise videos weekly, enabling near real-time batch tracking across AWS ECS environments. Integrated third-party CV engine (wrnch) for pose estimation and built a scalable parallel worker architecture, reducing video processing time through optimized batch sizing. Architected scalable AWS infrastructure using CloudFormation, supporting multi-version CV engine deployment with auto-scaling ECS clusters handling up to 500 concurrent jobs during peak loads.

ML Research Intern at Indian Institute of Science (IISc), Jun 2023 - Jul 2023 · 2 mos, Bengaluru, Karnataka, India, Worked on autoencoders and understood about neuromorphic computing and it's applications.

Samsung Prism intern at Samsung R&D Institute India, Nov 2022 - May 2023 · 7 mos, Bengaluru, Karnataka, India, Built a machine learning model to predict the optimal WiFi access point, solving the “sticky band” problem by automatically switching to the best available network. Exposed the model via a Flask-based REST API for seamless client integration. Developed an Android application (Java) to scan nearby WiFi networks and push structured signal data to MongoDB in real time for centralized processing. Designed and implemented a backend ETL service to clean and transform raw WiFi scan data, extracting relevant features and preparing high-quality datasets for model training and inference.

ML Intern at G-KnowMe, Nov 2022 - Dec 2022 · 2 mos, Bengaluru, Karnataka, India, Worked with OpenCV, OCR, NLP and Flask API during internship.

Project Intern at Dassault Systèmes, Mar 2022 - Aug 2022 · 6 mos, Bengaluru, Karnataka, India, Funded Project titled : “Smart Aqua Shrimp farming using Intelligent swarm fish for ecosystem monitoring and disease predictions”. -> Tested various transfer learning approaches to narrow down on a model for custom detection of Shrimps, foreign objects. The model was also trained to identify existing diseases in shrimps. -> The mode was deployed on a local host computer that communicated with a Raspberry pi on the fish robot using socket programming to send live images from the under water shrimp farm.

Education

Bachelor of Engineering - BE, Electrical and Electronics Engineering, B. M. S. College of Engineering

HSC, Science, kendriya vidyalaya