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AI Research Engineer with 4+ years in Data Science & Machine Learning
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Assessing your cultural and operational fit
Highly skilled AI/ML Engineer with 4.25 years of experience in developing and deploying advanced AI solutions. Proven expertise in building RAG systems, AI voice agents, and product analytics platforms, leveraging a wide array of tools including Python, LLMs, Vector DBs, and cloud services (AWS, Azure, GCP). Passionate about driving innovation, optimizing performance, and ensuring data privacy in production-grade AI applications.
Lahore University of Management Sciences (LUMS)
MS Electrical Engineering · Machine Learning, Software Engineering for Smart Grids, Computer Architecture, Digital Image Processing, Deep Learning
N/A – June 30, 2024
COMSATS Institute of Information Technology
BS Computer Engineering · Object Oriented Program, Data Structures and Algorithms, Web Engineering
N/A – Present
Bytewise Technologies
Sr. AI/ML Engineer
July 1, 2025 – Present
Lahore, Punjab, Pakistan
ASLASE
Machine Learning Engineer
April 1, 2024 – July 31, 2025
Lahore, Punjab, Pakistan
XStak Inc.
Data Scientist
February 1, 2022 – January 31, 2024
Lahore, Punjab, Pakistan
Vector Similarity Search using BERT Multilingual Model
June 24, 2026 – Present
Implemented vector similarity search with XLM-RoBERTa for semantic representation and optimized retrieval speed through cache memory.
LangChain Q&A Agent over Documents
June 24, 2026 – Present
Used LangChain to address ChatGPT's limitation by performing Q&A over unstructured data.
Analysis and Design of Sleep Stage Classifier using Machine Learning Algorithms (Master's Thesis)
June 24, 2026 – Present
Developed a non-invasive EEG-based processor using a machine-learning classifier to classify sleep stages for neurodegenerative disorder treatment.
Building toward Computer Use with Anthropic
Anthropic
February 1, 2025 – Present
Multi AI Agent Systems with CrewAI
CrewAI
November 1, 2024 – Present
Building Agentic RAG with LlamaIndex
LlamaIndex
September 1, 2024 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from RAG systems and AI voice agents to wellness assistants and recruiting agents, indicates a broad interest in applying AI across various domains. Their continuous learning through certifications (Anthropic, CrewAI, LlamaIndex) shows a commitment to staying current with industry trends. The experience in both academic and industry settings, including a Master's thesis, suggests a blend of theoretical understanding and practical application, which aligns well with an AI Research Engineer role that often requires both innovation and implementation.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills through complex system design and optimization. Their experience in leading development and improving efficiency suggests good operational fit. The diverse project portfolio indicates adaptability and a proactive approach to learning new technologies. The focus on production-ready systems implies a strong understanding of reliability and scalability.