Hi, I'm Smriti.
MS Computer Science @ Northeastern University
Software Engineer · ML · Data Science
I build systems that scale, models that ship, and sometimes both at the same time.
From fault-tolerant distributed stores to real-time legal translation pipelines — I've built across the stack. I build reliable systems, ship ML models end to end, and make data tell a story.
Highlights
A few things I've built along the way
Projects
- sustained, 0 failures
- 537 req/s
- replay mismatches in 39k events
- 0
- p95 fraud scoring
- 6.2 ms
Production-grade event-sourced payment ledger with CQRS, idempotent transactions, crash-safe transfer sagas, and real-time XGBoost fraud scoring — built on Spring WebFlux, Kafka, PostgreSQL, and Redis.
- operations checked linearizable
- 1.94M
- median leader failover
- 139 ms
- node cluster
- 5
Fault-tolerant key-value store in C++20 with Raft implemented from scratch: leader election with pre-vote, log replication and a replicated state machine across a 5-node cluster. 1.94M operations verified linearizable under 16 SIGKILLs and 43 network partitions, with leader failover in a median 139 ms.
- injected faults caught live
- 12 / 12
- median detection delay
- 9.9 s
- incident recall in benchmark
- 0.99
Self-hosted observability platform for microservices. Ingests logs, metrics, and traces via Kafka, processes them in real-time with Spark Streaming, and detects anomalies using Isolation Forest ML.
Implemented a distributed client-server architecture to analyze performance metrics under varying loads. Conducted comprehensive benchmarking of throughput, latency, and resource utilization.
Tech Stack
Languages
Backend & Distributed
Databases
Cloud, DevOps & Testing
ML & Data
AI
Education
Master of Science
Computer Science
Northeastern University · Boston, MA
RELEVANT COURSEWORK
Bachelor of Technology
Computer Science
Dayananda Sagar University · Bangalore, India
RELEVANT COURSEWORK
Certifications
Research Publications
Environmental Impact Analysis using Satellite Image Processing
IEEE 4th ASIANCON 2024
Developed automated workflows for environmental monitoring using satellite imagery, demonstrating applications in deforestation tracking and urban development analysis.
Optimising Computation Offloading for Mobile Edge Devices
ICAECT 2024
Researched and proposed optimization strategies for computation offloading in mobile edge computing environments, addressing latency and resource constraints.
Let's Connect
I'm actively seeking opportunities in Software Engineering, Machine Learning, and Data Science. Let's discuss how I can contribute to your team!