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AI Engineer with less than a year in Generative AI & MLOps
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Assessing your cultural and operational fit
AI/ML Engineer specializing in Generative AI, agentic pipelines, and MLOps. Proven track record of building end-to-end intelligent systems from fine-tuning neural networks to architecting scalable multi-agent LLM pipelines on AWS and GCP.
Namal University
BS Electrical Engineering
N/A – June 30, 2026
T8 Launchpad (NASTP Delta)
Trainee AI/ML & DevOps Engineer
February 1, 2026 – Present
Lahore, Punjab, Pakistan
Elevvo
NLP Intern
September 1, 2025 – October 1, 2025
India
AI Study Notes Agent
June 25, 2026 – Present
Architected a multi-user cloud-native study assistant leveraging Gemini 2.5 Flash and Search Grounding APIs for real-time, context-aware document analysis. Engineered a RAG pipeline using LangChain and ChromaDB (gemini-embedding-001) for persistent semantic search and accurate citations across large textbook libraries. Integrated Supabase for OAuth 2.0 authentication and persistent chat session management, and automated Anki flashcard generation from AI-produced notes.
View ProjectASL Recognition using Deep Learning
June 25, 2026 – Present
Designed a real-time sign language recognition system using five MPU6050 sensors to capture complex hand and finger motion data with signal preprocessing and feature extraction. Implemented classification using custom LSTM and CNN architectures, and deployed the trained model on a Jetson Nano for low-latency edge inference.
AuraBeat
June 25, 2026 – Present
Built an AI music curation platform that fuses real-time mood input, live weather data, and geolocation into an LLM context window for personalized soundscape recommendations via YouTube. Implemented dynamic UI aesthetic injection, BPM/energy controls, mood history sidebar, and Last.fm integration for enhanced music discovery.
View ProjectNeural Forensics V6.0
June 25, 2026 – Present
Built an agentic forensic suite with an 8-stage automated inspection pipeline and dual-track reasoning engine to detect AI-generated, manipulated, and enhanced imagery. Implemented interactive forensic sliders for visual evidence inspection and high-confidence verdict generation with structured PDF evidence export. Deployed full-stack application with a Next.js frontend on Vercel and a FastAPI backend on Render, running entirely on free-tier infrastructure.
View ProjectTrafficGuard AI
June 25, 2026 – Present
Built an AI-driven urban crisis intelligence platform at a hackathon that detects and analyzes severe flash floods and traffic blockages in Pakistani cities. Designed and deployed a React frontend and FastAPI backend on GCP Cloud Run, enabling real-time disruption simulation and mitigation recommendations powered by Gemini.
View ProjectGoogle Cloud: Engineer AI Agents with ADK
Google Cloud
January 1, 2026 – Present
Google Cloud: Develop GenAI Apps with Gemini and Streamlit
Google Cloud
January 1, 2026 – Present
Google Cloud: Prompt Design in Vertex AI
Google Cloud
January 1, 2026 – Present
Google Cloud: Explore Generative AI with Vertex AI API
Google Cloud
January 1, 2026 – Present
Google Cloud: Infrastructure Modernization
Google Cloud
January 1, 2026 – Present
Getting Started with Mistral
Unknown
January 1, 2025 – Present
Oracle Cloud Infrastructure AI Foundations Associate
Oracle Cloud Infrastructure
January 1, 2025 – Present
LangChain for LLM Application Development
Unknown
January 1, 2025 – Present
Understanding and Applying Text Embeddings
Unknown
January 1, 2025 – Present
ChatGPT Prompt Engineering for Developers
Unknown
January 1, 2025 – Present
Cultural Fit Analysis
The candidate demonstrates a strong cultural fit for an AI Engineer role, particularly in an innovative and fast-paced environment. The breadth of personal projects, ranging from AI study agents to forensic suites and real-time recognition systems, showcases curiosity, initiative, and a passion for applying AI to diverse problems. The experience with both AWS and GCP, along with various AI frameworks and tools, indicates adaptability and a willingness to explore different technologies. The current role as a Trainee AI/ML & DevOps Engineer further aligns with the practical, deployment-focused aspects often required in modern AI teams.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive and self-driven individual capable of end-to-end system development. The hackathon project (TrafficGuard AI) suggests an ability to work under pressure and deliver results. The detailed descriptions of architectural choices and deployment strategies imply good problem-solving and operational awareness. However, without direct interview data, specific soft skills like teamwork, leadership, or conflict resolution cannot be fully assessed.