AI
Open to full-time roles · 2026
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Software Engineer · Applied AI · Full-Stack

Sai SujithaNalajala

MS Computer Science, Indiana University Indianapolis. I build things at the intersection of applied AI, full-stack engineering, and systems that matter — from healthcare ML pipelines to browser-native AI products. I care about craft, shipping, and real impact.
98% ML accuracy · clinical research
200+ Students mentored
3.80 Final semester GPA · May 2026
Python PyTorch React.js LangChain XGBoost FastAPI AWS SHAP · LIME Docker Causal Inference TypeScript PostgreSQL Apache Spark Node.js Python PyTorch React.js LangChain XGBoost FastAPI AWS SHAP · LIME Docker Causal Inference TypeScript PostgreSQL Apache Spark Node.js
About
Engineer.
Builder. Researcher.

I'm a software engineer with a Master's in CS who came up building real things — not just coursework. My research is a healthcare ML pipeline that achieves 98% accuracy on chronic kidney disease prognosis using causal inference and explainability techniques that let clinicians actually trust the output.

I care about the full stack. From model architecture and API design to the React component a nurse clicks. I've shipped browser-native AI apps, led cross-functional teams, and mentored hundreds of engineers-in-training.

Currently based in Indianapolis, IN. Open to full-time software engineering, applied AI, and ML engineering roles. OPT eligible immediately.

Outside of engineering, I enjoy reading books, building funny and experimental websites, and turning random creative ideas into interactive web experiences.

— 01
Applied AI depth
XAI, causal inference, LangChain, RAG — built in real research contexts, not tutorials. I understand what models get wrong and why.
— 02
Full-stack execution
React, FastAPI, Node.js, microservices, AWS, Docker — from data model to deployed UI. End to end, no handoff required.
— 03
Ships things
Five live deployed applications. Automated grading systems in production. 30% faster evaluation pipelines. Real users, real impact.
Experience
Where I've
built.
Dec 2025 — Present
Indiana University Indianapolis
ML Research Engineer
TensorFlowXGBoostSHAPLIMEDoWhyCausal Inference
  • Architected comparative ML framework across 5 model classes for CKD prognosis — 98% predictive accuracy.
  • Built XAI reporting pipeline (SHAP + LIME) translating black-box outputs into clinically meaningful insights. Research publication in progress.
Sep 2024 — Present
Indiana University Indianapolis
Team Manager
Agile/ScrumCross-functionalData-driven delivery
  • Led engineering team — increased sprint velocity 85%, 100% on-time milestone delivery.
Aug 2024 — May 2025
Indiana University Indianapolis
Python Teaching Assistant
PythonDSAPyTestAutomation
  • Mentored 200+ students in Python, OOP, DSA. Automated grading pipeline — cut eval time 30%.
Sep 2023 — Jan 2024
Solar Secure Solutions
Data Science Intern
GCPREST MicroservicesSQLAnalytics
  • Deployed REST microservices on GCP. 25% system performance boost via SQL optimization. Built C-suite analytics dashboards.
Aug 2022 — Jun 2023
PVPSIT
Frontend Developer
React.jsAngularD3.jsChart.js
  • Built Student Information System serving 300+ users with real-time D3.js analytics dashboards.
Selected Work
Things I've
shipped.

Every project is deployed and live. Not slides, not mockups — real products with real users.

05
001
Healthcare AI · Research
CKD Prognosis — ML + Causal Inference

End-to-end pipeline combining supervised learning and causal reasoning for chronic kidney disease. Compared scikit-learn, XGBoost, Bayesian networks, and DoWhy across 5 model classes. Full SHAP/LIME explainability layer that lets clinicians trust — not just use — the output. Research publication in progress.

98%
Predictive accuracy
5 model classes · clinical XAI
PythonXGBoostSHAPLIMEDoWhy
002
Browser AI · Adaptive UX
AI Mood Web App

Mood-adaptive web app dynamically modifying content and user flows based on emotional input. End-to-end browser AI with adaptive UX and intelligent interaction design. Shows AI woven into UX rather than bolted on top.

JavaScriptBrowser AIUX
Live ↗
003
Canvas · On-device ML
Fish Tank + ML Validation

Browser drawing experience with real-time ML model inference validating user-drawn characters — with real-time browser-native inference. Creative proof of on-device ML integration in interactive products.

Canvas APIJSML Inference
Live ↗
004
NLP · Backend · State Machines
Rule-Based Conversational Engine

Context-aware chatbot built in Python using finite state machines — 99.9% state consistency across dynamic multi-turn dialogue. Demonstrates that backend logic rigor produces better conversational reliability and conversational consistency.

PythonFSMNLPPyTest
005
Product · Frontend · Voice
Sarcastic Chat

A decision-making assistant with a personality. Structured response logic, distinct product voice, custom conversational logic. Proves that great product character is an engineering decision.

JavaScriptLogic DesignUI/UX
Live ↗
Toolkit
What I work
with.
AI / ML
Languages
Web & APIs
Data Eng.
Cloud / DevOps
AI / ML
PyTorch XGBoost SHAP LIME LangChain DoWhy TensorFlow scikit-learn Hugging Face OpenAI API Causal Inference Bayesian Networks
Languages
Python JavaScript TypeScript Java Go SQL C++ R
Web & APIs
React.js FastAPI Node.js Angular Flask REST APIs Microservices Streamlit D3.js Chart.js
Data Engineering
Apache Spark Airflow Kafka ETL Pipelines MongoDB DynamoDB PostgreSQL Feature Engineering
Cloud / DevOps
AWS Docker GCP CI/CD PyTest Tableau Power BI
Let's
Contact
Let's build
something real.

I'm actively looking for software engineering, applied AI, full-stack, and ML engineering roles starting 2026. OPT eligible. Based in Indianapolis, open to remote. I reply within 24 hours.