About

I am a Staff Systems & Machine Learning Engineer specializing in large-scale personalization, ranking, and ML platforms. Also, working on agentic AI systems and research on open source LLMs.

Currently, I design and build systems that serve millions of users, focusing on the intersection of theoretical modeling and practical engineering constraints.

Technical Focus

🏗 Systems Engineering

Scalable Architecture: Designing low-latency inference systems.
Data Infrastructure: Building robust pipelines for training and real-time serving.
MLOps: Automating model lifecycle from research to production.

🧠 Applied Machine Learning

Recommender Systems: Deep learning for collaborative filtering and ranking (Two-Tower, DLRM).
Natural Language Processing: LLM orchestration and retrieval-augmented generation (RAG).
Optimization: Multi-objective optimization for balancing engagement and business metrics.

🤖 Agentic AI Systems

LLM Agents: Building autonomous agents for complex tasks.
Open Source LLMs: Research and development of open source LLMs.
AI SDLC: Standardizing AI Software Development Lifecycle.

Philosophy

"Learn, build, share."

"The best systems are boring."

"Leave the codebase better than you found it."

"Hard work beats talent when talent doesn't work hard."

I believe in simple, predictable, and observable systems. Complexity should be introduced only when necessary to solve a specific problem, not for its own sake.