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Engineer Software

Toronto, ON, Canada
January 06, 2020

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Zain Kabani


University of Toronto HBSc – Statistics: Statistical Machine Learning and Data Mining Dec 2020 (expected) Relevant Coursework: Software Design, Databases, Machine Learning, Artificial Intelligence, Regression Analysis, Applied Statistics SKILLS

Programming Languages: Python, Go, Java, R, JavaScript Tools & Frameworks: Kubernetes, Docker, Helm, Jenkins, Spark, Pandas, TensorFlow, Scikit-learn OpenCV, Flask, Express, Angular EXPERIENCE

IBM Software Engineer Intern (Architecture and Infrastructure) May 2019 - Aug 2019

- Architect and Engineer for a platform designed to streamline machine learning workflows across teams and to standardize project delivery practices; presented and demoed this platform to a large client resulting in funding for over $1,000,000

- Engineered a modular data ingestion service for batch and streaming data with Apache Spark and Kafka using a microservices architecture; the standards defined as part of the service helped to relieve the need for a dedicated ETL team

- Deployed and configured Prometheus to collect cluster metrics and used Grafana to create custom dashboards for visualization; the data collected was used to determine resource allocation in various microservices

- Lead the introduction of using Jenkins to enable test driven development and deployment automation as well as creating a software guidelines resource to encourage collaboration and use of industry best practices IBM Software Engineer Intern (Data Science) Sep 2018 - May 2019

- Configured deployment of JupyterHub on Kubernetes for a data science team of 10 to access cloud-hosted Jupyter Notebooks

- Provided support for deployment by fixing bugs and fulfilling feature requests such as notebook kernel configurations for clients

- Refactored OAuth authentication library in Python to enable use of IBM’s single sign-on service

- Developed a REST API in Go to manage and store user metadata for access control across various Kubernetes services

- Contributed to and collaborated on an open-source project, Jupyter Enterprise Gateway, by fixing bugs and implementing a feature to support configuration of Spark on Kubernetes IBM Machine Learning Engineer Intern May 2018 - Sep 2018

- Developed an object detection service using TensorFlow to extract data from hand-drawn maps which was used by a large client

- Implemented and trained several convolutional neural network models achieving over 90% mAP on a novel data set; used various neural network architectures and image preprocessing techniques with OpenCV to improve training

- Designed a novel approach for predicting orientation of objects achieving 98% top-3 accuracy on a 32-class model PROJECTS

NHL Worst Lead Analysis Python, Pandas, Matplotlib Oct 2019

- Used historical NHL game data to analyze which game leads resulted in the highest rate of losses

- Wrote an article on Medium sharing these findings reaching over 1500 views Vision AI (Hackathon) TensorFlow, Python, Flask, Google Home, Google APIs Aug 2018

- Winner of Best Use of Learning Hack at Hack the 6ix

- Used a deep learning model to generate textual description from an image and Google APIs for image-to-text and text-to-speech Student Leasing Website (Startup Idea) Node.js, Express, Angular, MongoDB, Google APIs Jan 2018

- Created a web platform to help landlords post listings and for tenants to find and lease listings electronically

- Designed back-end routes for CRUD operations on users and listings using MongoDB and Express

- - Implemented front-end feature in Angular to filter listings on a map using variety of search queries

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