Arsal Asif, Developer in Kitchener, Canada
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Arsal Asif

Verified Expert  in Engineering

Python Developer

Location
Kitchener, Canada
Toptal Member Since
July 16, 2020

Arsal is a software engineer with seven years of experience in research and software development. He has delivered high-quality, scalable solutions and results in fast-paced environments. Arsal's deep understanding of building, managing, and owning complex systems and his language-agnostic mindset allow him to adapt quickly to new tools and methodologies. Most importantly, his drive to take ownership of work sets him apart as a valuable asset.

Portfolio

Ada
Python, Python 3, MongoDB, NoSQL, Celery, Elasticsearch, Apache Airflow...
Gembah
Python, Celery, Redis, PostgreSQL, GraphQL, Django, Sentry, Datadog, Pusher...
University of Manitoba
LaTeX, Deep Learning, Computer Vision, Keras, Python, Algorithms

Experience

Availability

Part-time

Preferred Environment

Visual Studio Code (VS Code), Linux, MacOS, Git, PyCharm, GitHub, CircleCI, GitLab

The most amazing...

...thing I've built is an AI-driven SaaS application that scaled for millions of users and was used by companies such as Zoom, Meta, and Square.

Work Experience

Senior Software Engineer

2021 - 2023
Ada
  • Worked as a senior software engineer for a SaaS AI-driven brand interaction platform, mainly within a Python, Flask, and MongoDB stack.
  • Reduced the latency of multiple endpoints significantly with a maximum improvement of up to a 15x reduction in P99 latency.
  • Increased the test suite speed by 3x, from upwards of 22 minutes to around 5.5 minutes, saving developers hours in daily deployment and testing.
  • Designed and implemented the first-ever real-time update setup.
  • Set up Apache Airflow pipelines. Processed and ingested data at regular intervals, enabling the processing of millions of records daily.
  • Led an initiative to break up and decouple tightly coupled data models and endpoints.
  • Set up error tracking and code reliability through services such as Datadog and Sentry.
  • Assisted in building a secure application that passed SOC 2 compliance.
Technologies: Python, Python 3, MongoDB, NoSQL, Celery, Elasticsearch, Apache Airflow, CircleCI, GitHub, Data Modeling, Databases, Web Security, SaaS, Data Migration, Sentry, Datadog, Pusher, Flask, Algorithms, REST APIs, Continuous Delivery (CD), Jira, APIs, REST

Senior Back-end Engineer

2020 - 2021
Gembah
  • Developed parts of the back-end for an all-in-one platform for product creators, primarily with a Python, Django, and Postgres stack.
  • Improved latency by 30% by optimizing bottlenecked GraphQL queries.
  • Increased coverage of the codebase from 58% to 85%.
  • Streamlined testing by setting up a test infrastructure with pytest and factory_boy.
  • Improved infrastructure reliability and disaster recovery by integrating Datadog to report services and log analytics.
Technologies: Python, Celery, Redis, PostgreSQL, GraphQL, Django, Sentry, Datadog, Pusher, SQL, Databases, Algorithms, Continuous Delivery (CD), Jira, APIs, REST APIs, REST, Docker

Computer Vision Researcher

2018 - 2020
University of Manitoba
  • Conducted academic research in computer vision, video saliency, and depth estimation.
  • Created deep neural network architecture for a video saliency model, which quantitatively and qualitatively outperformed the state-of-the-art models.
  • Improved the previous benchmark by 15-30% on five different saliency metrics and three large-scale eye-tracking datasets.
  • Reported the best and recent deep learning approaches for depth estimation.
  • Identified the state-of-the-art methods in the field and provided a roadmap to the best available method.
  • Played a key role in improving the performance of the existing model by 10%.
Technologies: LaTeX, Deep Learning, Computer Vision, Keras, Python, Algorithms

Software Engineer

2016 - 2017
Techlogix
  • Designed, developed, and tested REST APIs for a SaaS application with millions of users.
  • Designed the back-end architecture for stock management, delivery, and distribution.
  • Handled complex SQL DML and SQL DDL database tasks. Wrote complex SQL stored procedures that greatly improved performance.
  • Created asynchronous methods to fetch and update the database.
  • Generalized and automated bulk uploading of entities by C# reflection.
  • Maintained code quality by employing tools such as SonarQube.
  • Supervised a team of juniors and worked closely with front-end developers.
  • Earned the “Achiever of the Month” award for excellence in performance.
Technologies: Git, SourceTree, Jira, Bitbucket, Jenkins, Liquid, REST APIs, Azure, JavaScript, .NET, C#, Databases, SQL, Algorithms, SQL DDL, SQL DML

Techlogix Enterprise Mobility

https://www.techlogix.com/enterprise-mobility/
A scalable SaaS model application I worked on as a software engineer. I focused on the back-end architecture built with C#, .NET, Microsoft Azure, and Microsoft SQL Server. I also designed, developed, and tested a REST API and supervised a team of juniors.

A Better REST API Boilerplate for Flask

https://github.com/arsalasif/flask-rest-api
I aimed to fix common pain points in building REST APIs with Flask. The project uses pluggable views, blueprints, decorators, and pydantic to modularize the Flask application and avoid repetition commonly associated with CRUD calls (based on the don't repeat yourself (DRY) principle).

Predicting Visual Saliency in Videos

http://hdl.handle.net/1993/34455
A research project to create a visual saliency model for predicting locations of fixations in eye-tracking datasets for videos. I built a static network for video saliency using deep neural network architecture that quantitatively and qualitatively outperformed the dynamic state-of-the-art models.

WordPress Automated Deployment Pipeline

https://github.com/arsalasif/wordpress-wpengine-deployment
Establishing an Agile workflow for WordPress is not a straightforward task due to WordPress' architecture. To that end, I created a WordPress automated deployment pipeline using the Bitbucket to WP Engine. I also created a Docker-based setup for local development.

Fantasy Football API with Flask

A RESTful API I developed for a fantasy football game.

My deliverables included:
• Containerized Docker builds with separate Docker services for the database, message broker, API, and documentation.
• Separate environments and configurations for development, testing, and production.
• Authentication via JWT.
• OAuth via Facebook and GitHub.
• Documentation via Swagger.

Languages

Python, C#, SQL, Bash Script, JavaScript, HTML, CSS, Python 3, GraphQL, SQL DDL, SQL DML

Frameworks

Flask, Django, .NET, JSON Web Tokens (JWT), Swagger

Libraries/APIs

Keras, SQLAlchemy, REST APIs, Liquid, Pusher, AMQP

Tools

Git, GitHub, NGINX, PyCharm, Jenkins, Bitbucket, Jira, SourceTree, Adobe Photoshop, Adobe Illustrator, Adobe InDesign, LaTeX, CircleCI, GitLab, Celery, Apache Airflow, Sentry

Paradigms

Agile, Testing, Continuous Delivery (CD), Continuous Integration (CI), Management, Back-end Architecture, Agile Workflow, REST

Platforms

Amazon Web Services (AWS), Azure, Docker, MacOS, Linux, Visual Studio Code (VS Code), WordPress

Storage

Databases, PostgreSQL, NoSQL, Redis, MongoDB, Elasticsearch, Datadog, Microsoft SQL Server

Other

Research, Machine Learning, Neural Networks, Algorithms, Computer Vision, Deep Learning, Leadership, Data Modeling, Web Security, SaaS, Data Migration, Microsoft Azure, Team Management, Deep Neural Networks, Gunicorn, APIs

2018 - 2020

Master's Degree in Computer Science

University of Manitoba - Winnipeg, Canada

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