LLM Research Scientist @ Gen Digital (MoneyLion) | Multi-Agent AI Architect | AIOps & Infra | Scaling AI from Research to Production | Fintech
I build AI systems that actually work in the real world — scalable, intelligent, and production-ready.
🎯 Currently: Developing large-scale LLM pipelines at Gen Digital (MoneyLion) to power real-time financial decision systems.
🧠 Expertise: Large language models (LLMs), Generative AI, multimodal intelligence, and multi-agent architectures.
🌍 Applications: Applied these methods in healthcare (e.g., radiology report generation), video-understanding (e.g., sign language recognition) and now focused on fintech, building high-performance agentic systems for enterprise deployment.
- 🧭 Designing multi-agent systems that coordinate LLMs.
- 🧠 Developing multimodal architectures that fuse vision, language, and structured data.
- 🏗️ Scaling research to production with PyTorch (DDP/FSDP), LangGraph, Kubernetes, AWS, etc.
- ⚡ Optimizing inference pipelines for low-latency, high-throughput real-world applications.
- 🧩 Building agentic workflows and infra that make AI systems reliable and efficient.
| Category | Tools & Frameworks |
|---|---|
| Programming Languages | Python • Java • TypeScript • JavaScript • HTML • CSS |
| Databases & Storage | MySQL • PostgreSQL • MongoDB • QDrant |
| Data Processing & Visualization | NumPy • Pandas • PySpark • Matplotlib • Seaborn • Plotly |
| AI/ML & GenAI | Scikit-Learn • PyTorch (DDP, FSDP, DeepSpeed, Ray) • LangChain • LangGraph • FastMCP |
| AIOps & Deployment | MLflow • Airflow • Docker • Kubernetes • Terraform • AWS |
| Other | Git • GitHub • GitHub Actions • Kafka • LaTeX • React • FastAPI |
“Great systems aren’t just built — they’re designed, debugged, and evolved.”