My Career

Nexus Laboratories Inc., San Francisco, USA

• Cryptography Engineer (Jun. 2025 to Present)
• Series A startup backed by Lightspeed, Pantera and Dragonfly
• Working as the lead backend engineer in implementing and maintaining the services required for the Nexus DEX and handling the devOps and system design using Kubernetes clusters, TiDB and Redis Cache
• Formulated and implemented the matching algorithm, liquidation, funding rates, and auto-deleveraging for the decentralized exchange
• Designed and implemented the on-chain oracle and the indexer optimized to keep up with the sub-second block times for the Nexus L1
• Working alongside the zkVM team in researching, implementing, optimizing, and benchmarking various proof systems
• Improving the user experience and onboarding of 2M+ users in NexusOS and building dApps
• Worked on the Testnet III distributed proving network and rewards system for 200K+ users
• Skills: Rust, RETH, NextJS, TypeScript, GCP, Solidity, Hardhat

Amazon Development Center, Chennai, India

• Software Development Engineer Intern (Jan. 2023 to Jun. 2023) [Certificate]
• Worked in Full-Stack Development as a part of the 6-membered SQS-CTT under the Digital Support Engineering Division.
• Was managed by Shalini A P and advised by Vivek Sunderraj.
• Investigated and implemented an efficient technique to record page-level metrics across 3 applications at minimum cost, saving 5 hours per week of manual analysis.
• Enhanced the processing and visualizing of 30+ web vitals, 500+ frequently occurring errors, and navigation trends of 12000+ active users, using AWS CloudWatch RUM.
• Developed ‘Insights and Conversations’ feature for 1100 internal testers and 200+ stakeholders to raise concerns and record insights on 13 testing metrics and start interactive conversations on the insights.
• Skills: Java, ReactJS, NodeJS, TypeScript, RESTful APIs, MySQL, AWS, Docker

Samsung Research Institue, Bangalore, India

• Project Intern (May. 2021 to Nov. 2021) [Certificate]
• Worked in collaboration with Samsung R&D's IoT team, as a part of the 'Samsung PRISM' program.
• Was managed and advised by Suyambulingam Rathinasamy Muthupandi.
• Conceived a novel machine learning model that makes decisions to execute JavaScript compute units locally or remotely by predicting and comparing the time of execution in the local machine and 7 different servers by analyzing execution time of 10000+ executions of similar complexity algorithms in each machine/server.
• Achieved an accuracy of 87.1% in predicting the execution time of a given application in multiple devices using a single model and an accuracy of 89.2% in making the correct offloading decision and received a Certificate of Excellence for the work done in solving the offload decision making problem and reducing the average time to execute a compute unit by 37%.
• Skills: Flutter, ReactJS, Python, PyTorch, Machine Learning, Internet of Things