Salman
Mubashir
AI 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 :
- Entropic: AI Developer.(Oct 2024 — Present)
- Solar Supplies & Services SMC: Trainee Engineer.(May 2023 — Jul 2023)
Education :
- BS Electrical Engineering (Computer Engineering major)National University of Computer and Emerging Sciences (FAST NUCES)(Sep 2020 — Jun 2024)
Work
Projects (case studies)
Each case study is structured: problem → approach → impact, with tradeoffs and next improvements.
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
PROGRAMMING
Python · React JS · Node JS · Tailwind · SQL
APIS
REST APIs · FastAPI · Flask · Postman
ML
PyTorch · TensorFlow · Keras · Scikit-learn · Hugging Face
DATA
Pandas · NumPy
CLOUD
AWS · GCP · Azure
TOOLING
Docker · Git · Selenium
DATABASES
Supabase · PostgreSQL
SOFT SKILLS
Logical reasoning · Collaboration
LANGUAGES
English (Fluent)
Recognition
Awards
FAST NUCES Gold Medalist
Fall 2022
- • Medal for the highest GPA score
FAST NUCES Gold Medalist
Spring 2023
- • Medal for the highest GPA score