AI/ML Engineer & Solutions Architect

Building systems where math meets production — from denoising astronomical images to multi-role pharmacy networks with transactional integrity at scale.

• 🧠 Specialization: ML Pipelines, RAG Architecture, Distributed Systems
• ☁️ Focus: Google Cloud GenAI, Vertex AI, LLM orchestration
• 🔬 Research: Convolutional Autoencoders + YOLO for astronomical object detection
• 📍 Location: DACH Region (MSc Student — USI Lugano)

Generative AI Engineering Intern — Google Cloud Track, NASSCOM FutureSkills (Jun–Jul '25)

• Built & evaluated RAG pipeline prototypes using Gemini + Vertex AI
• Designed structured evaluation frameworks for faithfulness & multimodal document quality

Swasthya — Multi-Role Pharmacy Network

• LightGBM demand forecasting + Isolation Forest anomaly detection as versioned microservices
• Normalized relational schema, row-level security, REST API on Google Cloud Run
• Gemini API integration for AI-assisted clinical Q&A

EcoShare — Community Credit Platform

• PostGIS geospatial analytics, proximity-based ranking, spatial clustering
• Atomic credit-transfer logic, escrow engine, NGO auto-matching algorithm

RAG Pipeline + Evaluation Harness

• Production-ready RAG with RAGAS metrics: hallucination detection, relevance scoring

LLM Benchmarking Dashboard

• Latency, accuracy, cost-per-query, safety alignment across providers

Languages: Python · TypeScript · Java · SQL · Bash
AI/ML: PyTorch · TensorFlow/Keras · Scikit-learn · LightGBM · HuggingFace · LangChain
Cloud: Google Cloud (Vertex AI · BigQuery · Cloud Run) · AWS Bedrock · Azure AI
Databases: PostgreSQL · Supabase · MongoDB · Pinecone · Milvus · PostGIS
Tools: Git · Docker · Jupyter · React Native · Expo

"Good architecture is invisible. Great ML systems feel inevitable."

Let's build something intelligent together 🚀