Salman
Mubashir
AI & Full-Stack Engineer — I turn data into intelligent products that ship, scale, and create measurable impact.

About
About Me.

I build intelligent systems across Computer Vision and NLP, and I’m comfortable owning the full path from data → model → API → product.
I bring 2 years of AI development experience and a portfolio of shipped work across AI systems, automation pipelines and applications. Outside of engineering, I reset through travelling and sports.
Experience :
- Al-Tahqeeq: CTO & Lead Developer.(Mar 2026 — Present)
- Paragon: Full-Stack Engineer.(Jul 2026 — Present)
- Vyka Diamonds: Full-Stack Engineer.(Mar 2026 — May 2026)
- Entropic: AI Developer.(Oct 2024 — Feb 2026)
Education :
- BSc Electrical Engineering (Computer Engineering Major)FAST NUCES (National University of Computer and Emerging Sciences)(Sep 2020 — Jun 2024)
Work
Projects (case studies)
Each case study is structured: problem → approach → impact, with tradeoffs and next improvements.
AlTahqeeq
Source-grounded AI answer engine for authenticated Islamic Q&A that cites every claim to its original source.
Sub-3% error rate with zero fabricated citations on a citation-linked hadith knowledge base.
View case study →
GluonAI
AI-powered email marketing platform with campaign management, an editor, and generation of on-brand content + HTML designs.
70% reduction in email template creation time.
View case study →
Tenderz Scraper
Modular tender scraping + AI extraction suite: download, validate, chunk, and convert tender docs into CSV/JSON reports.
40+ procurement platforms supported with multi-format document extraction and structured outputs.
View case study →
RAG System for Document QA
Local-first document QA with embeddings + vector retrieval and grounded LLM answering.
88% answer relevance score (define methodology).
View case study →
VisionMap
3D Earth interface that generates narrated video tours from prompts using an AI media pipeline.
AI-powered video tour generator (Unity + RunwayML).
View case study →
Epilepsy Seizure Detection
Deep learning model for neonatal EEG seizure detection with explainability for clinician trust.
82% accuracy, 85% sensitivity.
View case study →
IFS Therapist Assistant
Streamlit-based assistant that guides users through structured IFS sessions with safety checks and session management.
11-step guided IFS flow with automated step progression and safety flagging.
View case study →
SpectrumSense AI
RF signal analysis system: I/Q → spectrogram → CNN modulation classifier + autoencoder anomaly detector with a Streamlit UI.
RF modulation classification + anomaly detection on RadioML 2016.10a (11 modulation types, 220,000+ samples).
View case study →
Toolbox
Skills & tooling
AI & ML ENGINEERING
Generative AI · RAG Pipelines · Agentic Workflows · Arabic NLP · PyTorch · LangChain · Vector Databases (Qdrant / PGvector) · Prompt Engineering
FULL-STACK DEVELOPMENT
Python (FastAPI / Django) · TypeScript · React · Next.js · Node.js · REST / gRPC APIs
CLOUD & DEVOPS
GCP · AWS · Azure · Docker · Kubernetes · Terraform · CI/CD Pipelines
DATABASES
PostgreSQL · Supabase
TOOLS & FRAMEWORKS
Git · Shopify · N8N · Hugging Face · Postman · Scikit-learn · Keras · Pandas · NumPy · TensorFlow · Selenium WebDriver
SOFT SKILLS
Logical reasoning · Collaboration
LANGUAGES
English (Fluent)
Recognition
Awards
Gold Medalist, Spring 2023 Semester
Jun 2023
- • FAST NUCES, Islamabad
- • Medal for the highest GPA score.
Gold Medalist, Fall 2022 Semester
Jan 2023
- • FAST NUCES, Islamabad
- • Medal for the highest GPA score.