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Mayank Kainth

Software Engineer

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About Me

Computer Science graduate from Toronto Metropolitan University with 2 years of professional experience, a strong academic record, and expertise in software engineering, data analysis, and robotic engineering. Passionate about developing scalable software, intelligent automation, and cutting-edge robotic systems. Seeking a Software Engineering position where I can apply and grow my technical skillset to build innovative, high-impact solutions.

Experience

May 2023 - August 2024

Software Engineer (Co-op)

ECCC Logo Environment and Climate Change Canada · North York, Toronto, ON

  • Engineered and deployed the Unified Radar Processor (URP) system to process critical data from Canada’s national weather radar network, supporting advanced meteorological forecasting, aviation safety, and public protection.
  • Optimized system performance by proactively implementing code fixes and enhancements, aligning with industry best practices and project benchmarks.
  • Collaborated with cross-functional teams to drive improvements in scalability and reliability, ensuring robust system performance.
  • Developed robust code quality by writing unit tests, conducting pre-release testing, and creating detailed documentation.
  • Streamlined project workflows through prompt ticket resolution and active participation in code reviews.

September 2021 - April 2022

Data Scientist (Co-op)

OPG Logo Ontario Power Generation · Pickering, ON

  • Conceptualized and launched the ‘TWEEKs’ solution to automate report generation for part risk analysis, significantly boosting productivity and stakeholder communication.
  • Engineered automation processes to streamline supply chain housekeeping by extracting and analyzing historical outage data to identify low-stock items and flag surplus inventory.
  • Coordinated with vendors and project leaders to expedite part deliveries, optimizing shipping timelines for the Darlington Nuclear Refurbishment of Units 1 and 3.

Projects

Remote Control Bomb Defusal Robot

Undergraduate Thesis Project

  • Modified MATILDA robot chassis with tracks, remotely operated via ExpressLRS protocol using Radiomaster remote control.
  • Real-time video streaming using mounted cameras and Raspberry Pi via private WiFi.
  • Designed and 3D-printed carbon fiber robotic arm (2 DOF + claw).

GameScout

Steam Video Game Recommender System

  • Built within 24 hours, implementing collaborative and content-based filtering with Scikit-learn.
  • Used Python, NumPy, Pandas, Matplotlib, and Jupyter Notebook for data analysis.
  • Deployed as interactive web app via Flask.

Netflix Movie Recommender System

A dynamic web app recommending Netflix titles based on user ratings and viewing history.

  • Integrates both collaborative and content-based filtering techniques for improved recommendations.
  • Preprocesses and analyzes large datasets with Pandas, ensuring fast performance.
  • Features an interactive UI built with Streamlit for seamless user experience.

Vector Space Model Search Engine

Python-based search engine using an advanced Vector Space Model approach.

  • Implements robust tokenization, stop-word removal, and TF-IDF weighting for accurate query matching.
  • Processes queries and outputs the top-10 most relevant documents efficiently.
  • Includes custom pre-processor and inverted index modules for optimized performance.

VALORANT Auto Music Player

Automatically plays or pauses music based on the game state in VALORANT.

  • Monitors game state by interfacing with Windows API and parsing OpenCV video feed.
  • Automatically adjusts playback to sync with round transitions in the game.
  • Offers customization options for playlists and volume controls via a Tkinter GUI.

CyberFlag

A comprehensive platform designed to educate youth on cybersecurity.

  • Developed as a team project for the 2020 Digital Convergence Hackathon.
  • Fosters safe online practices for youth during increased online activity during the COVID 19 pandemic.

Poker Hand Solver

A high-performance Rust-based program that identifies the winning poker hands.

  • Efficiently evaluates and ranks poker hands using optimized algorithms.

Computer Vision Object Recognition

An OpenCV-based application for real-time object recognition and detection.

  • Utilizes deep learning models alongside traditional computer vision techniques.
  • Supports model fine-tuning and custom training for specialized applications.
  • Features a user-friendly interface for visualization and interaction.

Skills

Python

C

C++

Java

HTML5

CSS3

JavaScript

PHP

Flask

MySQL

Docker

AWS

Other Skills

  • Embedded Systems & Microcontroller Programming (Arduino, Raspberry Pi, ESP32)
  • Git version control
  • 3D printing and model design
  • Database Systems Management
  • Data Science
  • VSCode, Vim, Jupyter Notebook
  • VirtualBox
  • PowerBI
  • Microsoft Word, Excel, PowerPoint
  • Adobe Premiere and Photoshop

Education

TMU Logo

Toronto Metropolitan University (formerly Ryerson University)

Sept 2019 – Apr 2025 · BSc Computer Science (Honours)

Contact Me

Please contact me directly at mayank.kainth@torontomu.ca
contact me through +1-(647)-206-3327.