NG
Open to Internship

Hi, I'm Nikhil Ghind 👋

MS in Software Engineering @ SJSU · Software Engineer

Seeking a Summer 2026 software engineering internship as an SJSU MS student, leveraging senior-level experience in enterprise apps, distributed systems, and AI integration.

About

I'm pursuing an MS in Software Engineering at San José State University, focusing on Machine Learning. With five years at Interactive Brokers building enterprise systems that process $500M+ daily, I bring hands-on experience in distributed systems, API development, and AI integration.

Seeking a Summer 2026 software engineering internship to apply my enterprise background and ML studies to build reliable, scalable products.

Education

San Jose State University

Master of Science in Software Engineering

Focus: Machine Learning

Aug 2025 — May 2027 (Expected)San Jose, CA

University of Mumbai

Bachelor of Engineering in Computer Engineering

Aug 2016 — May 2020Mumbai, India

Skills

Languages

Java 17
Python
TypeScript
JavaScript
SQL

Frameworks & Libraries

Spring Boot
Spring MVC
React
Angular
AngularJS
FastAPI
Next.js

Databases

PostgreSQL
MySQL
MongoDB
Redis
Elasticsearch

Tools & Platforms

Docker
Kafka
Git
CI/CD
Apache Lucene
MLflow

Cloud & Infrastructure

AWS
Vercel
Linux

Machine Learning

LightGBM
Scikit-learn
SHAP
Pandas
NumPy

Experience

Interactive Brokers

Software Engineer
July 2020 — June 2025

FHSA Account Integration

→Built a standalone Spring Boot application to automate FHSA fund allocation, eliminating manual processing, saving 60+ hours/week, reducing errors by 90%, and delivering $75K+ in annual cost savings.
→Implemented a scalable FHSA microservice using the Adapter pattern, accelerating integration of new tax-advantaged accounts and ensuring regulatory compliance.
→Engineered customer-facing Angular UIs for creating FHSA transfers, replacing operator ticket workflows and eliminating manual handling—cutting transaction time by 90% and reducing manual effort.
Java 17
Spring Boot
Angular
Microservices
Design Patterns
Backend Development
Regulatory Compliance

Open Banking Integration

→Integrated Plaid's SDK into IBKR's AngularJS app (Payment Initiation, Auth, Identity), implementing secure token exchange and resolving embedded-browser quirks for a smooth Open Banking flow.
→Built a Spring Boot–based deposit-processing service for Open Banking across GBP, EUR, PLN, DKK, NOK, and SEK, supporting 500K+ users and enabling HSBC's brokerage partnership with IBKR.
→Integrated the services with the company's observability stack (Elasticsearch + Kibana), standardizing structured logs and adding Python-driven dashboards and alerts to improve time-to-detect and reduce MTTR.
Open Banking
Plaid SDK
AngularJS
Python
Elasticsearch
Kibana
API Integration
Backend Development
Software Architecture

Deposit Matching

→Designed and maintained a Spring-based project composed of small Spring packages, applying Abstract Factory, Factory Method, and Singleton patterns to isolate integrations and configuration; wrote JUnit tests and added a dedicated "regression" Spring profile for consistent regression testing.
→The project was responsible for processing all deposits across 23 currencies (≈$500M+ daily volume); upgraded the codebase from Java 8 to Java 17, improving performance, security, and maintainability and reducing incorrect or incomplete allocations by 30%.
Java 17
Spring Boot
Design Patterns
JUnit
Microservices
Performance Optimization

Apache Lucene Caching Service

→Built a refreshing cache with Apache Lucene and Spring Boot that caches about 100,000 deposit requests every 10 minutes, cutting downtime by 90% and increasing throughput. Reworked query structure and cache policy to reduce match latency from 2.8 seconds to 1.4 seconds and trim about 4 hours off service startup.
Java 17
Spring Boot
Apache Lucene
Caching
Performance Optimization

Operator UI Enhancement

→Enhanced a Spring MVC + AngularJS UI used by 25 global operators, adding multilingual, multi-currency, and account-type support; streamlined workflows.
Spring MVC
AngularJS
Multi-currency Support
Frontend Development
Software Engineering

AI Ops PoC (MCP Chat Orchestrator)

→Built a PoC MCP-based chat assistant using the client's Anthropic Claude model, integrating tools that expose internal allocation, cancellation, search, and linking endpoints so operators can complete tasks with simple prompts instead of complex screens.
AI Integration
Anthropic Claude
Workflow Automation
MCP
Software Engineering
API Development

Projects

Orbit - Productivity App

Cross-platform mobile productivity app with offline-first sync. Features task management, habit tracking, custom lists, and rich notes. Built with React Native frontend and FastAPI backend with PostgreSQL.

React Native
TypeScript
FastAPI
PostgreSQL
SQLite
Mobile Development

AI FlashTutor

AI-powered flashcard generator that turns PDF study materials into Q&A flashcards. Features LLM-powered card generation, speech-to-text, and text-to-speech capabilities using Cloudflare Workers AI.

TypeScript
React
Cloudflare Workers
AI/LLM
Vite
Serverless

Vehicle Seat Detection

Multi-model object detection pipeline for in-cabin seat occupancy detection using the SVIRO dataset. Compared YOLOv8, YOLOX, Faster R-CNN, RetinaNet, and EfficientDet, achieving 55.70% mAP@50 with Faster R-CNN.

Python
Computer Vision
YOLOv8
Faster R-CNN
Object Detection
Deep Learning

Nidana - Genetic Disorder Detection

AI-powered diagnostic portal for early detection of genetic diseases through facial feature analysis. Uses a 12-layer neural network with Keras for classification, featuring live camera capture and automated email reporting.

Python
Keras
Machine Learning
PHP
JavaScript
Healthcare AI

Go Screen Sharing

Zero-persistence, WebRTC-based screen sharing application with ephemeral room connections. Supports 1080p at 30fps with Go backend and React frontend.

Go
TypeScript
React
WebRTC
WebSocket
Docker

Crypto Price Prediction

Ensemble ML system for cryptocurrency price prediction using 6 base models (Random Forest, XGBoost, etc.) with 31+ technical indicators. Features purged K-fold validation and backtesting framework.

Python
Machine Learning
XGBoost
Random Forest
Data Science
Trading

Customer Churn Prediction

Predicted customer churn using tabular usage data, improving ROC-AUC from 0.74 to 0.87 with LightGBM, catching +22% more likely churners. Built a Streamlit app for CSV upload and SHAP explanations.

Python
Machine Learning
LightGBM
Streamlit
SHAP
Data Analysis

Real-Time Flight Delay Prediction

Developed ML system to forecast flight delays using U.S. flight records and hourly weather data. Achieved PR-AUC 0.42 and RMSE 11.8 min. Deployed model with FastAPI, Docker, and monitoring, handling 50 req/s with p95 < 60ms latency.

Python
FastAPI
Docker
MLflow
Evidently
Prefect
ML Deployment

Get In Touch

If you're considering my contribution, have a question, or just want to say hi, you can count on hearing back from me!

Or email me directly at nikhilghind19@gmail.com

Built with Next.js, Tailwind CSS, and Shadcn/ui, deployed with Vercel.