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AI Engineer with 4+ years in Deep Learning & LLM Development
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Highly skilled AI Engineer with 4+ years of experience in developing and deploying AI-driven solutions across diverse industries. Proven expertise in LLM training, fine-tuning, and prompt engineering, enhancing model accuracy and reliability. Adept at building end-to-end ML pipelines, computer vision systems, and AI automation workflows for real-world applications. Committed to leveraging deep learning and data engineering to deliver actionable business insights and drive innovation.
University of Wah
Bachelor of Science · Artificial Intelligence
N/A – June 30, 2025
Intercraft
Artificial Intelligence Engineer
January 1, 2025 – Present
Islamabad, Islamabad Capital Territory, Pakistan
Sirovista / Turing
Associate Software Engineer (LLM Trainer)
January 1, 2025 – Present
India
Arcelik R&D Center NUST
AI & ML Intern
August 1, 2024 – December 31, 2024
Islamabad, Islamabad Capital Territory, Pakistan
Fiverr & Upwork
Freelance AI/ML & Data Engineering Consultant
January 1, 2022 – Present
India
Autonomous AI Coding Agent for Full-Stack App Generation
January 1, 2025 – Present
Built an autonomous multi-agent coding system that generates complete full-stack applications (ERP, CRM, dashboards) from a single natural language prompt. Designed a LangGraph workflow with specialized agents for requirement analysis, code generation, QA validation, and Docker-based deployment. Implemented automated debugging and checkpoint-based version control using Docker log monitoring and conversational memory for iterative code refinement.
Dynamic Vision: Modular Real-Time Computer Vision System
January 1, 2024 – Present
Developed a modular real-time computer vision system for analyzing CCTV and video streams across multiple domains. Implemented detection modules such as suspicious activity monitoring, construction worker safety compliance, and sports motion analysis. Designed a decoupled architecture enabling independent deployment and extension of vision modules for different real-world use cases.
Automated Book Generation System
January 1, 2024 – Present
Designed an end-to-end AI automation pipeline to generate books (outline → chapters → final compilation) using n8n and GPT-4. Automated over 90% of the writing workflow, reducing manual effort and enabling multiple book generations with consistent quality. Integrated Supabase for real-time data storage and workflow tracking, ensuring reliability and scalability of the system.
Automated Multi-Domain Customer Support System
January 1, 2024 – Present
Built a multi-domain voice-enabled chatbot for customer service, adaptable to any business by integrating domain-specific knowledge bases. Integrated ChatGPT-4 with LangChain for RAG-driven responses and Twilio for handling real-time voice calls, enabling natural human-like conversations. Handled 75% of customer queries autonomously, validated through test call scenarios, by combining RAG-based knowledge retrieval with fallback escalation to human agents.
Enhancing Robot Localization with Deep Learning
January 1, 2024 – Present
Built a deep learning model to solve the robot kidnapping problem, predicting robot coordinates from LiDAR data and map inputs. Achieved 93.5% accuracy within 20px and 97.4% within 25px on custom datasets generated through simulation. Created and preprocessed large datasets, trained multiple architectures, and optimized models with early stopping and learning rate scheduling.
UFC Fight Analysis System
January 1, 2023 – Present
Achieved 90% accuracy in fighter detection using YOLO, enabling reliable tracking in recorded matches. Automated logging of 500+ fighter actions per match through integration of MediaPipe and OpenPose. Optimized performance with CUDA/cuDNN, reducing processing lag by 50% compared to baseline runs.
Deep Learning
University-led and external programs
January 1, 2026 – Present
AI
University-led and external programs
January 1, 2026 – Present
Cultural Fit Analysis
The candidate's diverse project portfolio, ranging from autonomous coding agents to real-time computer vision and customer support systems, indicates a strong curiosity and willingness to tackle varied challenges. Their freelance experience and contributions to national/international client projects suggest an adaptable and results-oriented mindset. The academic background in AI and continuous learning through certifications and workshops align well with a culture of innovation and continuous improvement. The candidate's ability to work remotely and in different company structures (internship, full-time, freelance) points to flexibility.
Soft Skills & Operational Fit
The candidate's project descriptions highlight problem-solving, system design, and the ability to work autonomously on complex AI challenges. Experience as a freelance consultant suggests strong client communication and project management skills. The role as an LLM Trainer indicates attention to detail and critical evaluation skills, which are valuable for operational quality assurance in AI systems. The candidate's involvement in government-sector initiatives and international client projects demonstrates an ability to work in diverse operational environments.