I’m a Software Engineer focused on ML systems and backend engineering, building production-style pipelines, evaluation frameworks, and infrastructure for machine learning workflows.

🎓 M.S. in Computer Science (AI), Hofstra University 💼 | AI Researcher at Algoverse | Former Software Engineer at Addact Technologies

🚀 What I work on

• ML Systems & Evaluation Infrastructure (RAG, LLM pipelines, benchmarking frameworks)

• Backend Engineering & APIs (ASP.NET, Python services, SQL-based systems)

• Data & Experiment Pipelines (reproducibility, orchestration, automation)

• Scalable & Reliable Systems

🧱 My background

• At Algoverse, I design and build modular, reproducible Python pipelines for evaluating LLMs across RAG and agent workflows, including data ingestion, batch execution, result aggregation, and automated validation tooling. My work focuses on experiment orchestration, reliability, and scalable evaluation infrastructure.

• At Addact Technologies, I worked on production backend systems using ASP.NET, C#, SQL Server, and Sitecore, building REST APIs, optimizing backend performance, and improving the reliability and maintainability of real-world applications.

📌 What you’ll find in my repositories

Most of my projects focus on:

• End-to-end ML systems and pipelines

• ML evaluation & experimentation infrastructure

• RAG and LLM tooling

• Backend services and data processing workflows

These are system-oriented projects, not just notebooks or demos.

🎯 What I’m interested in

I’m looking for roles at the intersection of software engineering and machine learning platforms, where I can work on:

• Infrastructure

• Pipelines

• Tooling

• Reliability

• Performance and scale

I care more about building reliable systems than just training models.