role: Software Engineer & AI/ML Systems Builder
location: Seattle, WA (Open to Relocate)
education: M.S. Computer Science @ Northeastern (Khoury College)
focus: Full-Stack Systems, Agentic AI, Multi-Agent Orchestration, RAG Pipelines, MCP Integration
research: Active β Generative AI
status: Open to Summer / Fall 2026 internships| βοΈ AI/ML Core |
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| πͺ Languages & Backend |
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| π Infrastructure |
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πͺ PersonaCR β Multi-Agent Code Review
6-agent system that learns your coding fingerprint and reviews code against your own patterns not generic rules. Research-grounded in 9 papers (EMNLP, NAACL, ACL). Parallel agent execution (~48% latency savings), CRScore-inspired ML quality gate (~69ms validation). Exposes full pipeline via MCP server (SSE transport) for direct Cursor/VS Code integration. ~8.5s end-to-end. |
π Third-Place-Finder β AI Recommendation Engine
Multi-stage RAG pipeline mapping natural language to structured categories, ranking top 10 with LLM rationale. Fault-tolerant integration with exponential backoff and anti-hallucination prompting. Deployed on Vercel + Render + Aiven. |
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π OULAD Analytics Engine β Concurrent Data Pipeline
Processes 10.6M rows at 2.1M rows/sec using producer-consumer architecture. 94% instruction coverage, 88% branch coverage with 51 tests including race condition harnesses. 3-person team. |
βοΈ Forest Fire Prediction β ML Risk Prediction
Wildfire prediction using 36K+ satellite records. RΒ² improved 0.65β0.68 via RandomizedSearchCV. Model compressed from 700MBβ93MB. Deployed via Django for real-time inference. |
| Role | Station | Mission |
|---|---|---|
| AI/ML Intern | IBM SkillsBuild | Built supervised ML models for healthcare risk prediction + IBM Cognos dashboards |
| Android Dev Intern | Google for Developers | Kotlin + MVVM apps with SQLite, REST APIs, unit & UI testing |
Program Manager β GameCube Club, Northeastern Β· Cloud Computing Lead β Google Developer Groups Β· Event Co-Lead β GDSC