Full Stack AI Engineer with 4+ years in LLMs, Computer Vision & Cloud MLOps
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Full Stack AI Engineer with 4+ years of experience building and deploying end-to-end AI-powered applications. Proven expertise in React frontends, Python/Node.js backends, and production-grade LLM integrations including RAG systems, vector databases, and prompt engineering pipelines. Experienced integrating cloud-based AI services (AWS SageMaker, OpenAI, Hugging Face) into scalable real-world products. Strong track record leading cross-functional engineering teams to ship multimodal AI features across computer vision, NLP, and conversational AI domains.
FAST-NUCES
MS · Artificial Intelligence
August 1, 2022 – June 30, 2024
Foundation University
BS · Computer Science
August 1, 2017 – June 30, 2021
Intercraft Pvt Ltd
Senior Machine Learning Engineer
December 1, 2025 – Present
Islamabad, Islamabad Capital Territory, Pakistan
Devsiom Technologies
AI Engineer
December 1, 2024 – June 1, 2025
Islamabad, Islamabad Capital Territory, Pakistan
AIO APP LTD
AI Process Automation Engineer
May 1, 2024 – December 1, 2025
Islamabad, Islamabad Capital Territory, Pakistan
National Electronics Complex of Pakistan (NECOP)
AI Intern
June 1, 2023 – July 1, 2023
Islamabad, Islamabad Capital Territory, Pakistan
Data Insight
ML Researcher - Generative AI
January 1, 2023 – May 1, 2024
Islamabad, Islamabad Capital Territory, Pakistan
LLM Fine-tuning & Vector Search Pipeline
June 1, 2026 – Present
Fine-tuned LLM on 50K+ samples using LoRA/QLoRA with semantic retrieval via FAISS embeddings; quantized model ran 3× faster than full-precision baseline for resource-constrained deployment.
Occluded Face Detection & Reconstruction (MS Thesis)
June 1, 2026 – Present
Two-stage pipeline using a detection model followed by a GAN to reconstruct masked facial regions; achieved 91% reconstruction quality (SSIM) on a 10K-image dataset.
Real-Time AI Video Dashboard
June 1, 2026 – Present
Led development of a VLM-powered system with React UI and async Python backend; supports natural language querying over live video streams with sub-second latency, deployed for enterprise clients.
Abusive Language Detection (NLP)
June 1, 2026 – Present
BERT-based text classifier; achieved 94% F1-score on a 100K-sample dataset using PyTorch and Hugging Face Transformers, deployed via FastAPI REST endpoint.
RAG-Powered Review Intelligence System
June 1, 2026 – Present
Built a Retrieval-Augmented Generation pipeline with FAISS vector store on 50K+ restaurant reviews; integrated LLM fine-tuned with LoRA/QLORA for context-aware response generation with 3× inference speedup via GGUF quantization.
Full-Stack Voice Chatbot
June 1, 2026 – Present
End-to-end voice assistant with React frontend and Python backend integrating STT, LLM reasoning with prompt engineering, and TTS; achieved <800ms round-trip latency in production customer support use cases.
AI For Everyone
Coursera
June 1, 2026 – Present
IBM Machine Learning Professional Certificate
IBM
June 1, 2026 – Present
Deep Learning & Reinforcement Learning
Unknown
June 1, 2026 – Present
Exploratory Data Analysis for ML
Unknown
June 1, 2026 – Present
Supervised ML: Regression & Classification
Unknown
June 1, 2026 – Present
Unsupervised Machine Learning
Unknown
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from academic research to personal projects and enterprise solutions, indicates a strong passion for AI and continuous learning. Their experience in leading teams and collaborating cross-functionally aligns well with a collaborative work culture. The breadth of skills across various AI domains (NLP, CV, Generative AI) and full-stack development suggests a versatile individual who can contribute to different aspects of a project, fostering a positive cultural fit.
Soft Skills & Operational Fit
The candidate demonstrates strong soft skills through their experience in team leadership, cross-functional collaboration, technical mentoring, and stakeholder communication. Their project descriptions highlight iterative prototyping and a focus on real-world deployment and performance metrics, indicating a strong operational fit for agile development environments. The diversity of projects, from real-time video understanding to voice chatbots and RAG systems, suggests adaptability and a problem-solving mindset.