Malik Shahzaib
Building intelligent systems at the intersection of software engineering and machine learning. Focused on scalable backend infrastructure, MLOps, and applied research in precision agriculture.
About Me
Software Engineer and ML Researcher with expertise in full-stack development, cloud infrastructure, and deep learning. Currently pursuing B.E. in Software Engineering at NUST (CGPA: 3.4/4.0) with hands-on experience at YC-backed Markaz Technologies and as a founding engineer. Selected for Mitacs Globalink Research Internship 2026. Published research in agricultural AI and actively working on LiDAR-based plant phenotyping systems. Passionate about bridging the gap between research and production-grade systems.
Bachelor of Engineering, Software Engineering
National University of Science and Technology (NUST)
Islamabad, Pakistan • Sep 2022 - Expected June 2026
CGPA: 3.4/4.0
Relevant Coursework:
Skills
Backend & Languages
ML & AI
Cloud & DevOps
Web Development
Experience
Globalink Research InternIncoming
Mitacs Globalink Research Internship
Winnipeg, Canada
- •Selected for a competitive international fellowship to work on the project titled data augmentation and deep learning for mechanical damage classification in seeds.
Software Engineer
Markaz Technologies (YC W22)
Islamabad, Pakistan
- •Developed Locatr, an LLM-powered API to resolve unstructured address data for the Markaz marketplace.
- •Migrated AWS Lambda functions to GCP Cloud Run, implementing a CDN layer that reduced API latency by 4x.
- •Engineered an image optimization pipeline converting Alibaba-hosted assets to WebP (reducing size by 40%), migrating storage to Google Cloud (GCP) buckets served via a custom domain CDN.
Founding Engineer
Elegant Intelligence
Islamabad, Pakistan
- •Leading the development of an MVP that automates legal contract generation and online dispute resolution.
- •Supervising the technical execution and product strategy for an MVP, meeting with industry experts and researching cutting-edge technologies to enhance features.
Undergraduate Researcher
Machine Vision & Intelligent Systems Lab
Islamabad, Pakistan
- •Conducting literature review of state-of-the-art models in precision agriculture, exploring deep learning approaches for LiDAR, hyperspectral, and RGB imagery.
- •Working with drone hardware integration: 3D printing components, mounting sensors (LiDAR, cameras), and deploying on NVIDIA Jetson Orin Nano for data collection.
Machine Learning Research Assistant
TUKL-NUST R&D Center
Islamabad, Pakistan
- •Trained deep learning models on the NMT scalp EEG dataset to classify between normal and abnormal EEG signals.
- •Developed a full-stack application (Vue.js, Flask, MySQL) to deploy the trained model for user interface.
Research & Publications
Published research in agricultural AI and precision agriculture using deep learning and LiDAR technology.
AgriFormer: Advancing 3D LiDAR-based Biomass Prediction through Hierarchical Feature Learning
Malik Shahzaib, et al.
Proposed a hierarchical Transformer-based model for processing 3D LiDAR point clouds to accurately estimate agricultural biomass, outperforming baseline models. Presented at the 22nd ACS/IEEE International Conference on Computer Systems and Applications in Doha, Qatar.
Certifications
Professional certifications in deep learning, machine learning, and full-stack development.
Featured Projects
A selection of projects showcasing full-stack development, ML engineering, and cloud infrastructure with real-world impact.
LiDAR-Based Plant Phenotyping for Precision Agriculture
Developing a comprehensive and non-destructive pipeline for plant phenotyping using LiDAR technology from data collection to extracting meaningful insights.
Umeed - Marketplace for Rural Women Empowerment
A comprehensive marketplace platform designed to empower rural women by providing a digital platform for economic participation and skill-sharing in rural areas.
Get in Touch
I'm currently open to new opportunities, research collaborations, and interesting projects. Feel free to reach out if you'd like to connect.