Master's student in Computer Science @ Northeastern University
I'm passionate about the intersection of networking and machine learning infrastructure particularly in areas of distributed inference, model serving, and scalable AI systems. As a first-generation college student, my journey into tech has followed an unconventional path, transitioning from biochemistry to computer science.
My background spans bioinformatics research, network engineering, and now MLOps/cloud infrastructure. These experiences have shown me how much networking principles apply to scaling AI systems.
- Cloud ML Engineer Intern @ Centene Corporation — Deploying open-source LLMs on GPUs and building an end-to-end multi-model evaluation system to categorize and rank models
- Learning more about C++, inference optimization, networking and HPC
- Software Engineer Intern @ Microsoft — Infrastructure automation for network device compliance
- Network Engineer @ Vigitron — Built foundation in networking fundamentals, hardware (switches/cabling/routers), and automation
- Bioinformatics Researcher @ UCSD Gleeson Lab — Data pipelines for somatic structural variation detection
ConquestFour — 2nd Place, Qualcomm & Microsoft On-Device AI Hackathon
LLM-powered Connect Four using Mistral-7B (4-bit quantized). Implemented Minimax with Alpha-Beta pruning, Z3 validation, and OpenAI Whisper for speech-to-text. Optimized with ONNX Runtime for NPU execution.
Semantic Sounds — Personalized Music Recommender
Semantic recommender using SHAP-selected features, sBERT embeddings, and HDBSCAN clustering (Silhouette: 0.7464). Processed 60k+ Spotify entries.
Languages: Python, Java, C++, SQL, Bash, YAML, KQL
ML/Infra: MLflow, Databricks, PyTorch, Spark, ONNX, LLM Deployment & Evaluation
Cloud/DevOps: Azure, AWS, Docker, Kubernetes, Jenkins, Git, CI/CD
Databases: MongoDB, Postgres, Redis, Delta Lake
Networking: TCP/IP, VLANs, DHCP, ACLs, L2/L3 diagnostics
- Azure Fundamentals (AZ-900) — 2025
- Google Cybersecurity Certificate — 2024
Seeking full-time opportunities (graduating in 2026) in ML Infrastructure, MLOps, Cloud Engineering, or roles where networking and AI converge.