
Product · AI / ML
Portfolio
Scroll-driven CSS transitions and Mimir, a retrieval-only chat that answers with real passages and links.
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Building robust AI systems,
from research to production.
Open to full-time SWE / ML roles · 2027
Hi, I'm Mimir. Ask me about Aqeed's work, projects, skills or what he's looking for. I only answer from what's on this site.
Limited to this site: answers come straight from its content.
AI engineer at GPU IQ and Computer Science master's student at Rutgers, graduating May 2027. Day-to-day tools: Python, TypeScript, PyTorch, Next.js, PostgreSQL and the Claude API. Interested in LLM applications, retrieval and evaluation, data pipelines, and machine learning systems that hold up in production. Seeking a full-time ML, AI or software engineering role starting summer 2027.
in_my_element.gifRAG evaluation, LLM agents and token-budget-aware prompting, running in production.
Multi-tenant platforms: row-level isolation, Stripe billing and onboarding.
Full-stack SWE — Next.js and React through Django, Flask and PostgreSQL.
Benchmarking CNNs, Transformers and SSMs, and distilling models for the edge.
A live pipeline across all six US ISOs — scraping, county-level geocoding and scoring for 16,291 active projects.
Claude-powered, answering from live production signal data and routing visitors by intent to a booking or a self-serve signup.
Per-case chunk inspection and pass-rate diffing in server components — 78.25% across 400 logged evals.
Tenant isolation across 107 RLS-protected tables, with Stripe billing, onboarding and a meeting-bot pipeline on top.
Chat agents, RAG pipelines and eval harnesses
Isolation, billing, onboarding and auth
Ingestion, geocoding, training and evaluation loops
Model benchmarking, distillation and edge inference
UI to API to database, end to end

Product · AI / ML
Scroll-driven CSS transitions and Mimir, a retrieval-only chat that answers with real passages and links.

AI / ML
Heuristic search for grid localization: a learned heuristic expands about 95% fewer nodes than optimal search.

Product · Systems
A live Java auction site: bid by hand or set a secret auto-bid limit, across 1,740 real listings.

AI / ML
Five fraud models compared on 1M transactions, with precision-recall curves and a cost-based threshold.

Research · AI / ML · Systems
CNNs vs Transformers vs SSMs for edge inference, distilled into a small SSM: 65% to 85.3% accuracy.


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