engineer:
name: "Mohammed Umar F"
title: "AI Systems Architect & Multimodal ML Engineer"
core_philosophy: "Production-first intelligence β bridging scalable data architectures with frontier neural transformers."
specializations:
- multimodal_deep_learning: "Vision-Language fusion (DINOv2, ResNet34, DistilBERT, cross-attention)"
- information_retrieval: "Two-stage hybrid RAG (FAISS dense + SPLADE-v3 sparse + Cross-Encoders)"
- entity_resolution: "Million-scale record linkage with TF-IDF n-gram inverted indexing & Levenshtein"
- autonomous_agents: "Stealth Chrome MV3 DOM automation, GPT-4o-mini lead qualification & Supabase"
current_quest: "Scaling production multimodal inference pipelines, RAG systems, and enterprise agent workflows"| System / Repository | Domain & Focus | Core Architecture & Tech Stack | Key Metric |
|---|---|---|---|
|
π resume-ranker
Enterprise Two-Stage Hybrid RAG |
Information Retrieval |
Two-stage hybrid candidate retrieval: dense FAISS vector search fused with sparse SPLADE-v3 expansions, two-part Cross-Encoder reranking, and Qwen 2.5 synthesis. | 100% explainable candidate rankings |
|
π·οΈ Smart-Product-Pricing
Enterprise Multimodal Pricing Engine |
Amazon ML Challenge |
Dual-tower architecture fusing DistilBERT text embeddings with DINOv2 visual features via cross-attention, fed into gradient boosted LightGBM with Snappy Parquet streaming. | 0.38 RMSLE benchmark |
|
πΏ PlantDocBot
Multimodal Agronomy Diagnosis |
Infosys Springboard |
Dual-tower agronomy diagnosis platform fusing ResNet34 foliage visual classification with fine-tuned DistilBERT symptom extraction, dynamic confidence gating, and Streamlit UI. | 95.2% diagnostic accuracy |
|
π€ Eylo-Reddit-v2
Autonomous AI Growth & Outreach |
Agentic Systems |
Manifest V3 Chrome extension featuring anti-detection DOM humanizers, GPT-4o-mini intent qualification, and unified Supabase multi-account lead deduplication. | 10x qualified lead discovery |
|
π’ Business-Entity-Resolution
Million-Scale Merchant Deduplication |
Data Engineering |
Scalable record linkage pipeline combining TF-IDF n-gram inverted index blocking, Levenshtein distance matrices, and a gradient boosted classification reranker. | > 99% candidate pair recall |
|
π₯ nutritional-ai-agent
Autonomous Clinical Dietary Reasoner |
IBM Hackathon |
Autonomous multi-agent dietary assistant orchestrating biomarker ingestion, clinical constraint solvers, and adaptive recipe synthesis for personalized medical nutrition. | Zero contraindicated dietary plans |
- π₯ Amazon ML Challenge: Engineered a dual-tower multimodal pricing pipeline merging text transformers, self-supervised DINOv2 vision encoders, and cross-attention fusion models.
- π₯ Infosys Springboard Project: Developed PlantDocBot, a high-precision dual-tower agronomy diagnosis engine pairing ResNet34 (95.2% accuracy) with fine-tuned symptom NLP.
- π₯ IBM Hackathon: Architected an autonomous multi-agent clinical nutrition assistant orchestrating dietary biomarkers and medical reasoning constraints.
- π Eylo: Engineered autonomous Chrome MV3 stealth outreach automation with non-fingerprintable humanized interaction heuristics and GPT-4o-mini lead qualification.