Backend & distributed systems engineer with a master's in CS from NYU. I build reliable services, data pipelines, and the infrastructure they run on, with a soft spot for performance and systems that hold up under load.
🔭 Currently building event-driven backends and AI-powered features as a founding engineer 🌱 Interested in distributed systems, GPU/performance work, and applied AI
- StockMarket.ai — RAG app that recommends and summarizes stock-prediction research, grounding an LLM in a vector-searched corpus.
- CUDA Parallelization Prediction — predicts optimal CUDA launch configs with XGBoost + SHAP across seven GPU workloads.
- RepCRec — distributed database with replicated concurrency control, deadlock detection, and site failure/recovery.
- OS-Nexus — from-scratch C++ simulators of an OS scheduler, virtual-memory manager, I/O scheduler, and linker.
- M. Prajapati et al., "Automatic Question Tagging using Machine Learning and Deep Learning Algorithms," 2022 6th Intl. Conference on Electronics, Communication and Aerospace Technology (ICECA), 2022, pp. 932–938. DOI
- Languages: Python, Go, C/C++, C#, TypeScript, JavaScript, SQL, Java, Scala, Bash/Shell
- Backend & APIs: FastAPI, Spring Boot, Node.js, Flask, REST APIs, GraphQL, Microservices, System Design, Distributed Systems
- Data & messaging: PostgreSQL, MySQL, MongoDB, Redis, Kafka, Apache Spark, Airflow, ChromaDB, ETL
- Cloud & DevOps: AWS, GCP, Docker, Kubernetes, Terraform, Ansible, Jenkins, GitHub Actions, OpenShift, CI/CD
- ML & AI: PyTorch, Hugging Face, RAG, LLM Evaluation, LangChain, XGBoost, CUDA, GPU Programming, HPC
- Testing & observability: Pytest, JUnit, Selenium, Postman, Prometheus, Splunk, Grafana