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AI Engineer with 2+ years in LLMs, NLP & DevOps
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Mohammad Shayyan Bilal is an accomplished AI Engineer with 2.3 years of experience in designing and deploying AI-powered systems. His expertise spans across developing LLM-based chatbots, enhancing land acquisition platforms with document understanding, and building scalable workflow automation. He has a strong background in NLP, machine learning, and MLOps, with practical skills in Python, FastAPI, Flask, and cloud platforms like Google Cloud, backed by a Bachelor’s degree in Artificial Intelligence.
FAST National University of Computer and Emerging Sciences
Bachelor · Artificial Intelligence
September 1, 2020 – January 1, 2025
DiveDeepAI
Machine Learning Engineer
June 1, 2024 – Present
Islamabad, Islamabad Capital Territory, Pakistan
Eurus Technology
Devops Engineer
June 1, 2023 – September 1, 2023
Islamabad, Islamabad Capital Territory, Pakistan
RehnumaAI: Interactive Urdu Learning
January 1, 2024 – December 1, 2024
Developed an AI-powered educational platform with personalized learning experiences using adaptive content and real-time feedback mechanisms. Integrated NLP-based interaction modules to enhance user engagement and improve learning outcomes.
RAG-Based ChatPDF System
November 1, 2023 – December 1, 2023
Designed and implemented a Retrieval-Augmented Generation (RAG) system for PDF-based question answering using Large Language Models (LLMs). Built an end-to-end pipeline including document ingestion, vector embeddings, semantic search, and response generation using LangChain and CassandraDB.
AI-Driven Text Generation for Opinion Analysis
November 1, 2022 – December 1, 2022
Built an NLP-based system for sentiment analysis and automated text generation using machine learning techniques. Applied Natural Language Processing (NLP) to extract insights and generate context-aware summaries for decision-making.
Cultural Fit Analysis
The candidate's project diversity, ranging from educational platforms to RAG systems and sentiment analysis, indicates a broad interest in AI applications. Their academic background in Artificial Intelligence directly aligns with the target role of an AI Engineer. The experience at DiveDeepAI, though recent, shows engagement with complex AI system development and deployment, which is a strong fit for an AI-focused organization. The brief DevOps experience also suggests an understanding of the broader software development lifecycle, which is beneficial for team collaboration and integrating AI solutions into production environments.
Soft Skills & Operational Fit
The candidate demonstrates a proactive approach to learning and applying AI technologies, as evidenced by diverse personal projects and a relevant academic background. Their experience in a DevOps role, though brief, indicates an understanding of operational aspects crucial for AI system deployment. The descriptions suggest an ability to work on end-to-end solutions, from design to deployment and monitoring. However, the current experience is relatively short, and the descriptions, while detailed, could benefit from more explicit articulation of problem-solving approaches and collaborative efforts.