Dhruva Chaitanya G

About Dhruva Chaitanya G

I am a Full-Stack ML Engineer and iOS Developer who turns complex data problems into production-ready systems — fast, scalable, and built to perform under real-world conditions.With hands-on experience spanning machine learning, real-time inference, cloud architecture, iOS development, and full-stack engineering, I don\'t just build models — I ship complete solutions from data pipeline to deployed interface. I am passionate about pushing the boundaries of what AI can do in production, integrating Generative AI, MLOps, and serverless technologies into systems that real users depend on every day.Currently active in Chicago and open to opportunities globally. I thrive at the intersection of data science, software engineering, and emerging AI — leveraging machine learning to drive smarter product decisions, reduce operational cost, and create intelligent digital experiences that scale.Core Skills:ML & AI: Predictive Modeling, Real-Time Inference, Deep Learning, Fraud Detection, RAG AI, TensorFlow, PyTorch, Scikit-learn, MLFlow, ARIMA, Automated Retraining PipelinesDevelopment & Mobile: Full-Stack Web, iOS Development, React.js, React Native, Node.js, Python, REST APIs, WebSockets, Responsive UI, Component ArchitectureCloud & DevOps: AWS (SageMaker, Lambda, S3, API Gateway, CloudFormation), Docker, Apache Kafka, Redis, PostgreSQL, MongoDB, MLOps, CI/CD, Infrastructure as CodeTesting & Research: Jest, Postman, Chrome DevTools, Unit & Integration Testing, A/B Testing, Data Quality Monitoring, Published Research, Competitive AnalysisI combine engineering precision, deep curiosity, and a relentless builder\'s mindset to solve problems that actually matter — while staying ahead of the curve on AI innovation, cloud-native architecture, and intelligent product design.M.S. Data Science — DePaul University, Chicago. B.E. Electronics & Communications Engineering — PES University, Bangalore. Published researcher at an international AI and electronics conference. AWS Machine Learning Specialty certification in progress.If you are building something ambitious and need an engineer who can own it end-to-end — let\'s talk.DM or email me: d••••••@depaul.edu

Experience

1. Machine Learning Engineer

   Rypil

   Nov 2025 — Present · Chicago, IL, US

   Architected a production fraud detection system with real-time ML inference pipelines achieving sub-100ms latency, improving platform reliability and transaction security.• Built the frontend and backend of Rypil\'s iOS application using React Native, delivering core user flows and loyalty integration screens from API to interface.• Led end-to-end testing and debugging across staging and production, resolving critical UI/UX, API, and performance issues on the web platform.• Contributed competitive intelligence research that directly informed Rypil\'s market positioning and product strategy.

Education

• PES University

  Bachelor of Engineering - BE, Electrical, Electronics and Communications Engineering

• DePaul University Jarvis College of Computing and Digital Media

  Master of Science - MS, Data science