[Actively seeking full-time opportunities in Software Engineering, ML Engineering, AI Infrastructure, MLOps, Data Engineering, or Cloud roles] I'm an AI graduate and engineer with 3+ years of experience in cloud infrastructure, ML system development, and production-scale AI deployment. My work spans distributed systems, CI/CD pipelines, biomedical data integration, and scalable architecture design using open-source tools. I recently completed my MS in Artificial Intelligence at Oregon State University, where I contributed to NIH Translator schema mapping research and led a capstone project focused on real-time AI applications with Beaverhand, a startup partner. My academic journey sharpened my skills in applied ML, scalable data systems, and rapid prototyping. Previously at the National Payments Corporation of India, I designed and maintained high-availability systems that processed over 10M daily transactions. I implemented comprehensive observability platforms, led critical production support, and initiated research projects in distributed system design and fraud detection. I enjoy solving complex problems with simple, reliable solutions — whether it’s building real-time LLM applications, tuning performance across microservices, or shipping scalable ML infrastructure. I'm particularly excited about roles that merge engineering depth with ML application impact. Let’s connect if you're working on AI at scale, real-time data systems, or pushing the boundaries of cloud-native architectures. Core Skills & Tools: Python, SQL, PyTorch, TensorFlow, FastAPI, LangChain, Docker, Kubernetes, Terraform, AWS, Apache Airflow, MLflow, PostgreSQL, Kafka, MongoDB, C/C++