anushka ashirgade

I’m a Machine Learning Engineer focused on turning complex data and financial workflows into reliable, production-grade solutions. With a foundation in Machine Learning & AI and Financial Analytics from the National University of Singapore, I approach every problem with both modeling rigor and engineering discipline.

In my internship work, I supported real client engagements by scoping and delivering technical tickets that map client financial workflows into software solutions. I also implemented core DeFi payment services in Solidity, contributed to stablecoin peg stability mechanisms, and built backend services for cross-chain interoperability—resolving 50+ engineering tickets while maintaining robust architecture and compliance.

At SAP AI LABS, I strengthened production data and reliability by executing database migrations with Alembic and optimizing tenant batching workflows. I integrated Dynatrace monitoring across microservices to improve observability and production debugging, and I refactored a Python codebase to improve modularity and maintain code quality.

My projects reflect a balance of advanced ML and practical deployment thinking: multi-agent pipelines with LangGraph over large-scale datasets, multimodal emotion recognition for elderly care, safety-aware fraud detection model selection, and hybrid recommendation systems using both knowledge-graph and deep learning approaches. I want to keep building systems that are accurate, safe, and designed to run.