Feb 2023 – Mar 2025 · 2 yrs 1 mo · Mumbai Metropolitan Region

• ✼ Ultra High-Frequency Trading & Low-Latency Systems Engineer
• ✼ Infrastructure
• ✼ C++
• ✼ Distributed Systems
• ➺ FPGA-Based Market-Making Accelerator: Led development of an FPGA-based market-making accelerator, cutting tick-to-trade latency to sub-microsecond. Implemented multithreaded C++ applications for FPGA–trading system integration and firmware interfacing.
• ➺ Advanced Trading System Integration: Engineered a real-time order management system with ultra-low latency, integrating risk management, position control, and trade validation while optimizing tick-by-tick market data processing and routing logic.
• ➺ Quantitative Strategy Development: Spearheaded design and deployment of an FPGA-enabled multi-leg derivatives arbitrage strategy with near-instant responsiveness. Used C++ for development and R for performance analytics and model validation.
• ➺ Trade Reconciliation Engine: Developed a reconciliation engine using TCP sockets, improving firm-wide trade monitoring via real-time analytics, automated validation, and streamlined reporting workflows.
• ➺ Distributed Health Monitoring: Co-engineered a distributed framework for colocation monitoring, ensuring high availability and reliability through alerting, failover handling, and real-time incident response.
• ➺ TBT Market Data Management: Designed a scalable, fault-tolerant system to process and manage 2TB+ of tick-by-tick data daily, optimizing ingestion, compression, and retrieval for quantitative research.
• ➺ In-House Compliance Search Engine: Built a custom search engine automating compliance document retrieval and indexing, saving the compliance team 600+ hours annually.
• ➺ Legacy System Optimization: Upgraded a simulation market data streamer to gRPC and Protobuf, improving throughput, response time, and maintainability.
• ➺ Cross-Exchange Data Normalization: Built a dynamic system to normalize trading data across exchanges, ensuring accuracy, synchronization, and reliability for HFT operations.

Jul 2022 – Nov 2022 · 4 mos · Bengaluru, Karnataka, India

• ✼ Backend Engineer
• ✼ Infrastructure/Platform (Logistics)
• ✼ Golang/Ruby-On-Rails
• ✼ Distributed Systems
• ► Fixed potentially exploitable ends in Authentication Service and performed Database Optimization resulting in reduced space usage by 88% for storage of Authentication Details.
• ► Migrated existing features from a monolithic-based architecture to a new aggregated microservices-based architecture for operations.
• ► Implemented the functionalities for an upcoming system "Walker" in the Logistics Domain and it's inclusion in the existing microservices architecture and gateway aggregator.
• ► Improvised legacy code bases to modern development standards, improving functionality and reliability.

Mar 2022 – Jun 2022 · 3 mos · Remote

• ✪ Investigating liquid staking solutions to devise appropriate offering strategies for Stader's flagship liquid token FTMx for the Fantom Ecosystem.
• ✪ Evaluating existing token-flow of competitors and estimation of potentially-profitable partnerships with several Decentralized Exchanges and Liquidity Pools.
• ✪ Assisted in launch of Stader's Liquid Token on Fantom Chain resulting in $120 Million worth of $FTM token being staked on Stader platform over period of 2 months.
• ✪ Skills : Crypto, Web3, Market Analysis, Marketing

Jul 2021 – Dec 2021 · 5 mos

• ✪Samsung R&D Institute India – Bangalore
• ✪Part of The Data Intelligence Lab at the Services PF and Big Data Group.
• ✪Offered a Full-Time Developer Role at the end-of-tenure.
• ➟Researching techniques for Low Latency and Efficient Content-Based Image Retrieval in Large-Scale Image Databases using Feature Extraction.
• ➟Designed Feature Extracting Framework based on Deep-Learning using Convolutional Neural Networks.
• ➟Implemented Rapid Search Mechanisms (Hierarchical Navigable Small World Graphs, Inverted File Indexing, Product Quantization, Locality Sensitive Hashing) for Quick Retrieval in a highly dense Feature Space.
• ➟Built an end-to-end recommendation system by scripting and abstracting the complete pipeline as a RESTful API that can be integrated with the flagship app.
• ➟Domain : Deep Learning, Digital Image Processing, Computer Vision, Database Management
• ➟Tools/Technologies - TensorFlow, Python, Keras, PyTorch, Anaconda, Streamlit, Flask, Docker, Postman

May 2019 – Jul 2019 · 2 mos · Rourkela

• ► 8-Week long Research Internship at Steel Authority of India Limited (SAIL)
• ✪ Project involved studying and using PLC's for transmission of interlocking data to the remote locations of Rourkela Steel Plant and optimizing this transmission so as to reduce the transmission time without data loss which required extensive programming of PLC's in SIMATIC STEP-7
• ✪ Worked extensively under the Electronics and Electrical Services department to understand the use of various electronic components presently being used in RSP such as PLC's , Transducer's ,etc.
• ✪ Department visits to several departments in the plant such as Hot Strip Mill, Steel Melting Shops -I,II,III Cold Rolling Mill, Sintering Plant - I,II,III, Electronics and Electrical Services to gain exposure about the working process of these departments and the problems being faced by them and their possible solutions
• ✪ Received an 'A' grade & Recommendation for performance based on mentor and organization review

Mar 2019 – Jul 2019 · 4 mos

• ◆ Working remotely as a Research Consultant on WebSim platform making long-short equity trading strategies using fundamental & technical analysis
• ◆ Implemented Mean-Reversion, Behavioral Exploitation, US market news, Sentiment data and Fundamental Analysis for strategy modelling
• ◆ Used advance mathematical and statistical techniques to develop global macro, directional, event and relative value-driven signals
• ◆ Taking advantage of diversification across stocks, to produce a low-volatility investment strategy uncorrelated with the existing strategies pool