I am a software developper, passionate about programming and AI, with a special interest in solving complex problems and getting exposed to new information and topics. I have a strong foundation in full-stack development, working with agile and fast-paced environments, and in initiating new projects. Those qualities and experiences have driven my curious jounrey through the world of software development, writing code in collaboration with others to build software that helps the world.

• Programming Languages: C, Java, C#, Bash, SQL, Java, JavaScript, Python, FXML, VHDL.
• Frameworks & Tools: .NET, Django, FASTAPI, Unittest, Pytest, Docker, PostgreSQL, Postman, Cucumber, Scene Builder, PyTorch, Tensorflow, scikit-learn, pandas, PostgreSQL, NodeJS, JUnit, Gradle, JavaFX, JUnit, JWT.
• Other Skills: Microservices, Authentication/Authorization, BDD, TDD, Containerization, Migration.
• Languages: English (Fluent), French (Fluent), Arabic (Fluent).

Bachelor of Software Engineering | McGill University
Cumulative GPA: 3.81/4.0

Relevant Courses:

• Intro. to Software Engineering
• Algorithm Design
• Computer Organization
• Software Requirements Engineering
• Model-Based Programming
• Algorithms and Data Structures

Obytes Technologies | May 2024 – Aug 2024

• Migrated REST API suites from C#/.NET to Python/Django, optimizing time and memory complexity, managing URL routing and up to five-tier nested serializers
• Developed unit tests for new features using pytest, Django factories, mock objects, and YAML fixtures, validating functionality with database views and tables, edge cases, error handling, AWS S3 bucket management, authorization, permissions, and curl commands.
• Initiated and implemented a migration tool using Dockerfile, Makefile, and git hooks to streamline local database container migrations within Docker multi-container app, improving developer efficiency
• Documented custom authorization/authentication processes and JSON Web Token (JWT) handling to enable the team to begin implementation.

Inmind.ai | Jun 2023 – Aug 2023

• Integrated a querying and filtering application into databases managed using PostgreSQL, by implementing a suite of APIs using Python FASTAPI framework and ensured protection against SQL injection attacks.
• Built a proof-of-concept machine learning and computer vision binary image classification model for detecting bees and ants, using a pre-trained ResNet18 with data-augmentation in PyTorch. - Source Code
• Implemented principal component analysis (PCA), reducing dataset dimensionality for easier handling and training of Support Vector Machines (SVM), with feature extraction algorithms (HOG, Word2vec, Tf-Idf), built using scikit-learn, PyTorch and pandas.

McGill Robotics | Sep 2022 – Jan 2023

• Researched PID controls to address excessive strain on components caused by abrupt movements. Collaborated with a team of engineers to modelize the rover’s control mechanism and feedback loop, enabling a better understanding of rover positioning

A Full-Stack application for warehouse inventory, staff and client management.
Tech Stack: Java, FXML, JavaFx, Umple.

• Collaborated with developers to build a GUI JavaFx app following Model-View-Controller architecture based on Umple UML diagrams, using Gherkin, Cucumber, JUnit, and Scene-Builder software.

A chrome extension for monitoring and connecting users to a TPU runtime on google colab.
Tech Stack: JavaScript, Server-side, CORS, Google Cloud Functions.

• Developed a Chrome extension that automates checking TPU availability on Google Colab, it interacts with the website DOM to connect users to a runtime, and notifies them by email using Google Cloud serverless functions and the MailerSend API, using Google Developer Tools.

A custom built neural network for detecting 58 differnt food types in images.
Tech Stack: Python, Tensorflow, Keras, CNNs

• Implemented and analyzed Deep Learning models: Custom Convolutional Neural Networks (CNNs), EfficientNet and ResNet in categorical image classification of 58 food types, using TensorFlow and Keras.

• Essential Learning Technologies - ELT Founded an EdTech venture in collaboration with McGill’s TechAccel program, focusing on student’s challenges in Quebec at the post-secondary level leveraging LLM and AI technologies.
• Mentor at McGill Software Engineering co-op department Volunteered with the department to support and guide upcoming students as they embark on their professional journeys.

• Languages: C, Java, C#, bash, SQL, Java, JavaScript, Python, FXML, VHDL.
• Tools and Frameworks: .NET, Django, FASTAPI, Unittest, Pytest, Docker, PostgreSQL, Postman, Cucumber, Scene Builder, PyTorch, Tensorflow, PostgreSQL, NodeJS, JUnit, Gradle, JavaFX, JUnit, JWT.

• Email: [email protected]
• Mobile: +1 (438) 528-4279
• LinkedIn: Nicolas Saade
• GitHub: Nicolas-Saade

"Turning ideas into reality, one commit at a time."