Experience

Where the numbers came from

6 roles, 2 degrees and 8 certifications — each leading with what it actually moved.

Software Engineer

Current

Leadec

Mar 2025 – PresentSanta Clara, CA, USA

30xp99 latency cut150ms → <5ms

100+tenants isolatednamespace-level

+20%Recall@5hybrid retrieval

80%memory savedvs per-tenant DBs

Multi-tenant search infrastructure: Designed multi-tenant vector search service (Qdrant) with namespace-level isolation across 100+ independent environments; collection filters enforced strict data boundaries, reducing memory overhead 80% vs. per-tenant database approach
Hybrid search service: Built search service combining inverted-index keyword matching with semantic vector retrieval to handle exact alphanumeric codes and natural language in a unified pipeline; improved Recall@5 by up to 20% over vector-only architecture with no latency regression
Low-latency query routing layer: Engineered intent-classification service that routes requests before triggering expensive downstream calls; fast-path circuit breaker for direct-lookup queries reduced p99 retrieval latency from 150ms to <5ms (30x), eliminating vector search overhead for targeted file queries

PythonJavaPLC ProgrammingPandasNumPy

Software Engineer

BMR Infotek

Aug 2024 – Mar 2025Dublin, CA, USA

1M+records embeddedsentence transformers

3.5M+records/monthAirflow → Redshift

35%pipeline latency cutretry orchestration

+20%marketing ROIbehavioral targeting

Large-scale text processing pipeline: Built batch embedding pipeline processing 1M+ customer records using sentence transformer models; outputs fed a segmentation service enabling precision behavioral targeting that improved marketing ROI by 20%
Distributed data ingestion service: Designed Apache Airflow DAG-based ETL system on AWS EC2 ingesting and transforming 3.5M+ records/month into Redshift; retry orchestration and task-level fault isolation reduced pipeline processing latency by 35%
Model serving & versioning platform: Built orchestration service connecting forecasting model outputs to downstream consumers; CI/CD pipelines automated model versioning, artifact promotion, and rollback, enabling zero-downtime model updates in production

Machine LearningPowerBISQLDeep LearningRFM Modeling

Graduate Research Assistant

Kelley School of Business, Indiana University

Dec 2022 – May 2024Bloomington, IN, USA

100M+rows classifiedfine-tuned BERT

91%test precisioncampaign + sentiment

+15%predictive accuracyLLM analytics pipeline

Large-scale NLP & classification: Applied fine-tuned BERT models to a 100M+ row dataset for political campaign and sentiment classification, achieving 91% test precision
LLM-based analytics: Implemented LLM pipeline to analyze customer satisfaction and brand equity signals for large US companies; improved binary classification predictive accuracy by 15% and surfaced quantifiable financial market impact

NLPSeabornFeature EngineeringMachine LearningExcel

Full Stack Engineer Intern

Twin Cities Innovation Alliance

Sep 2023 – Dec 2023Minneapolis, MN, USA

+17%user engagementA/B testing framework

40%API latency cutNode.js → ML services

A/B testing infrastructure: Built traffic-routing framework across application variants; SQL-based conversion analysis drove a 17% lift in user engagement
Recommendation engine: Engineered collaborative + content-based filtering backend, optimizing preference retrieval queries to achieve 20% engagement increase
API performance: Developed Node.js RESTful APIs connecting frontends to ML microservices, cutting API response latency by 40% and driving 15% growth in daily active usage

Statistical ModelingA/B TestingSQLRecommendation Systems

Co-Founder and CTO

Moonplexus Pvt. Ltd.

May 2021 – Aug 2022Pune, MH, India

Healthcare platform: Designed microservices web platform (Java, Django, AngularJS, SQL) automating health information management; 40% reduction in query execution time through relational DB optimization
Cloud infrastructure: Migrated and maintained AWS EC2/RDS infrastructure, building fault-tolerant ETL pipelines with high availability for large-scale medical data storage
Deep learning deployment: Deployed TensorFlow/CNN diagnostic models via Docker with FastAPI endpoints, reducing inference latency by 30% and improving system uptime

TensorFlowAWS EC2 / RDSCNNNode.jsETL

Research And Development Intern

Indian Institute of Technology (IIT)

Oct 2020 – Apr 2021Guwahati, AS, India

Algorithm optimization: Researched and developed incremental/decremental versions of DBSCAN and MBSCAN algorithms in Python and C++ for distance-based outlier mining
Clustering performance: Improved computational speed by 30% and precision by 20% in clustering algorithms; tested optimizations on a fintech application with 1M+ users for customer segmentation and portfolio optimization

PythonC++ClusteringData AnalysisMachine Learning

Academics

Education

Master of Science, Computational Science

Indiana University Bloomington

Aug 2022 – May 2024

Key coursework: Applied Machine Learning, Elements of AI, Probability & Statistics, Big Data, Data Warehousing & Mining, Business Intelligence

Bachelor of Technology, Computer Science & Engineering

MIT World Peace University

Jul 2018 – Jun 2022

Key coursework: Data Warehousing & Mining, Business Intelligence, Big Data Analysis, Financial Econometrics, Design & Analysis of Algorithms, Database Management

Credentials