Belal Esawe, Developer in Vancouver, BC, Canada
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Belal Esawe

Verified Expert  in Engineering

Machine Learning Engineer and Developer

Vancouver, BC, Canada
Toptal Member Since
June 21, 2023

Belal is a senior machine learning engineer with over eight years of experience who has successfully delivered cutting-edge solutions to renowned brands like Gucci and Armani. His expertise in image classification, segmentation, NLP, and data analysis enables him to drive innovation and enhance businesses. With a PhD in computer engineering focusing on machine learning, Belal brings to the table a strong research background that successfully prompts him to tackle complex challenges.


The Reynolds and Reynolds Company - Main
Machine Learning, Natural Language Processing (NLP), Python...
Python, Amazon Web Services (AWS), Google Cloud, Machine Learning...
Python, Amazon Web Services (AWS), Google Cloud, Machine Learning...




Preferred Environment

Linux, Visual Studio Code (VS Code), Slack, Zoom

The most amazing...

...system I've built is Complete-the-look, a game-changing product that transformed the shopping experience and captivated renowned brands like Armani Exchange.

Work Experience

ML/NLP Technical Lead

2023 - PRESENT
The Reynolds and Reynolds Company - Main
  • Developed and deployed a chatbot leveraging OpenAI and LangChain to automate and enhance customer service efficiency.
  • Implemented customized assistants by fine-tuning GPT models, reducing queue wait times and improving customer satisfaction.
  • Utilized prompt engineering techniques to tailor assistants to emulate chat operators, adhering to established protocol guides for professional and rapid customer support.
  • Integrated assistants with customer databases, enabling real-time access and personalized service delivery.
Technologies: Machine Learning, Natural Language Processing (NLP), Python, Generative Pre-trained Transformers (GPT), Machine Learning Operations (MLOps), SpaCy, Natural Language Toolkit (NLTK), Redis, MySQL, New Relic, ClickHouse, ChatGPT, Large Language Models (LLMs), OpenAI, Artificial Intelligence (AI), LangChain, Generative Artificial Intelligence (GenAI), Hugging Face, OpenAI GPT-3 API

Lead Machine Learning Engineer

2020 - 2023
  • Developed ML-driven products that resulted in a provable 5-22% revenue lift for clients.
  • Created recommendation engines delivering personalized products, driving increased sales and customer satisfaction.
  • Implemented innovative solutions leading to 250 million weekly site visitor predictions.
  • Transformed data insights into actionable strategies, resulting in improved conversion rates.
  • Collaborated with cross-functional teams to identify business needs and align ML solutions accordingly.
  • Streamlined processes, reducing time-to-market for new product features.
  • Led research and development (R&D) efforts, staying ahead of industry trends and delivering cutting-edge ML systems.
  • Communicated results and achievements to stakeholders, building trust and inspiring confidence.
  • Mentored team members, fostering their growth and driving impactful contributions.
Technologies: Python, Amazon Web Services (AWS), Google Cloud, Machine Learning, Computer Vision, CI/CD Pipelines, Natural Language Processing (NLP), TensorFlow, Keras, Convolutional Neural Networks (CNN), Supervised Machine Learning, Machine Learning Automation, PyTorch, Artificial Intelligence (AI), Videos, OpenCV, Pandas, Deep Learning, APIs, Natural Language Toolkit (NLTK), SpaCy, AI Programming, OpenAI GPT-4 API, Data Science, Generative Pre-trained Transformers (GPT), Machine Learning Operations (MLOps), Recommendation Systems, Image Generation, Generative Artificial Intelligence (GenAI), Image Processing, Data Pipelines

Lead Machine Learning Engineer

2020 - 2022
  • Developed an AI-powered product leveraging data fusion techniques to automate mapping and quantification of damage on concrete structures, enabling faster and more accurate inspections.
  • Implemented advanced algorithms that significantly reduced inspection time and costs for infrastructure owners while maintaining high accuracy levels.
  • Collaborated with cross-functional teams to gather and integrate diverse data sources, optimizing the performance and reliability of the damage detection system.
  • Validated the product's effectiveness through extensive testing and evaluation, achieving a high accuracy rate.
  • Streamlined the data processing pipeline, enabling seamless integration with existing infrastructure inspection workflows and maximizing operational efficiency.
  • Provided technical expertise and guidance to clients, facilitating the successful implementation and utilization of the AI-based damage assessment solution.
  • Conducted thorough analysis of inspection results, generating comprehensive reports and visualizations to aid decision-making and prioritize maintenance efforts.
  • Monitored and incorporated user feedback, continuously enhancing the product's capabilities and user experience.
  • Presented the product's success and benefits to infrastructure owners and industry professionals, fostering strong partnerships and driving adoption across the sector.
  • Contributed to the advancement of the field by publishing research findings and presenting at conferences, solidifying my reputation as a thought leader in AI-driven infrastructure inspection.
Technologies: Python, Amazon Web Services (AWS), Google Cloud, Machine Learning, Computer Vision, QGIS, MATLAB, TensorFlow, Keras, Convolutional Neural Networks (CNN), Supervised Machine Learning, Machine Learning Automation, PyTorch, Artificial Intelligence (AI), OpenCV, Pandas, Deep Learning, AI Programming, Data Science, Image Generation, Generative Artificial Intelligence (GenAI), Image Processing, Cloud Point, Data Pipelines

Machine Learning Engineer

2017 - 2020
  • Spearheaded the development and implementation of an AI-based mineral alteration mapping product, resulting in increased sales and revenue generation for the company.
  • Streamlined the process of mineral alteration mapping using AI techniques, significantly reducing project timelines and enabling faster decision-making for clients.
  • Positioned the AI product as a key driver of business growth, attracting new customers and expanding market reach.
  • Demonstrated the value and impact of the AI solution through data-driven results, leading to improved client satisfaction and increased repeat business.
  • Transformed the way geospatial data is analyzed by leveraging AI technology, driving efficiency and accuracy in mineral exploration and resource extraction projects.
  • Conducted in-depth analysis of sales data and customer feedback to identify areas for product enhancement and revenue optimization.
  • Established PhotoSat as a leader in AI-driven mineral alteration mapping, contributing to the company's reputation for delivering fast, accurate, and revenue-generating geospatial solutions.
Technologies: Python, Remote Sensing, QGIS, TensorFlow, Keras, Convolutional Neural Networks (CNN), Supervised Machine Learning, Machine Learning Automation, PyTorch, Artificial Intelligence (AI), OpenCV, Pandas, Deep Learning, AI Programming, Data Science, Image Generation, Image Processing, Remini

Automatic Product Tagging

An automatic product tagging solution that uses advanced AI models to extract main categories and attributes from any product catalog, eliminating the need for manual tagging. This innovative solution automatically generates accurate tags, simplifying catalog management, saving valuable time, and enhancing efficiency and organization. It is a cutting-edge solution that revolutionized how product tagging is handled by replacing manual efforts with seamless automation and transforming the workflow of product categorization.

Recommendation System
An eCommerce personalized recommendation system that, leveraging historical user interactions, processes vast data to deliver tailored recommendations. Through advanced algorithms, it analyzes purchase history, browsing habits, and demographics to generate accurate product suggestions, enhance customer satisfaction, drive sales, and foster loyalty with personalized recommendations that resonate. This system elevates eCommerce platforms, provides a dynamic shopping experience, and unlocks new growth opportunities in the competitive market.

An innovative product designed for eCommerce customers. Powered by machine learning, this system revolutionizes the shopping experience by seamlessly scanning outfit images and conducting a product search. It intelligently identifies all items within the image and presents them in a captivating carousel called Complete-the-look. This way, customers can effortlessly explore and purchase the entire outfit, enhancing convenience and style cohesion. Embracing the future of fashion shopping, where visual inspiration transforms into a seamless purchase journey, this system elevates eCommerce platforms by offering a curated shopping experience that drives conversion.

Remote Sensing Applications for Geospatial Analysis
A system that uses AI models to detect water bodies and produce accurate digital elevation maps (DEM). This solution streamlines the process by automating waterbodies detection in satellite imagery, allowing geospatial analysts to focus on data analysis. With precise zero-leveling of waterbodies, the project enhances DEM accuracy, benefiting hydrology, environmental modeling, and land management applications. I revolutionized geospatial analysis with this innovative project, optimizing workflows and delivering valuable insights for informed decision-making.

Mineral Alteration Mapping
This innovative solution utilizes AI models to analyze multispectral satellite images, enabling spectral matching and precise mineral detection. By harnessing data from satellites like WorldView-3 and ASTER, this game-changing project targeting professional geologists in mining unveils unique spectral signatures for various minerals.

As it leverages rich multispectral data, Mineral Alteration Mapping aids exploration, resource estimation, and mining planning. With this system, geologists can efficiently detect and map mineral alteration, significantly reducing time and costs in the industry.

By automating the process, advanced AI models analyze the satellite images, providing invaluable insights into mineral presence and distribution so that geologists can focus on in-depth analysis and decision-making, bolstering productivity and accuracy.

Ultimately Mineral Alteration Mapping optimizes mineral exploration and mining operations and empowers geologists with an efficient tool to identify and map minerals, unlocking new discoveries and resource management opportunities.

Craft Your Game Character

I employed stable diffusion and Null-Text Inversion techniques to generate and/or locally edit characters. Furthermore, I leveraged a fine-tuned Language Model on character dialogues to create a chat style that aligns with the selected character.

By utilizing these advanced methodologies, I achieved impressive results and delivered high-quality outcomes for my client. My approach not only demonstrates technical proficiency but also emphasizes the ability to create engaging and dynamic content.

I believe that my expertise and passion for machine learning, combined with my strong problem-solving skills, make me the ideal candidate to undertake this project. I am committed to delivering exceptional results and exceeding your expectations.

I would welcome the opportunity to discuss your project requirements in more detail and showcase how my skills align with your needs. Thank you for considering my candidacy, and I look forward to the possibility of collaborating with you.

Defects Mapping in Infrastructure
In this project, I focused on defect mapping in infrastructure. Leveraging the power of AI, I developed a robust system capable of mapping various types of defects, such as cracks, spalling, efflorescence, and joint failures. This model has been trained on a vast amount of data collected from diverse assets worldwide, ensuring its adaptability to different factors such as construction material, time of day, weather, and shadows.

By utilizing AI technology, this system can automate the process of identifying and quantifying defects in infrastructure assets like dams, chimneys, roads, and buildings. Accurately mapping defects is crucial in ensuring these assets' safety and structural integrity while simultaneously reducing the time and cost associated with manual investigations.

Through this project, on the one hand, I provided customers with valuable insights by quantifying defects and sorting them based on severity. On the other hand, by presenting defect information in a systematic and organized manner and evaluating and prioritizing defects, I empowered engineers to efficiently assess the condition of infrastructure assets and take appropriate actions.
2014 - 2020

PhD in Computer Engineering

University of Victoria - Victoria, BC, Canada

2012 - 2014

Master's Degree in Science

University of Northern British Columbia - Prince George, BC, Canada


TensorFlow, Keras, PyTorch, OpenCV, Pandas, Natural Language Toolkit (NLTK), SpaCy


Slack, Zoom, ChatGPT, MATLAB, Remini




Data Science


Linux, Visual Studio Code (VS Code), Amazon Web Services (AWS), New Relic


Data Pipelines, Google Cloud, Redis, MySQL, ClickHouse


Machine Learning, Computer Vision, Research, Complex Problem Solving, CI/CD Pipelines, Natural Language Processing (NLP), Convolutional Neural Networks (CNN), Supervised Machine Learning, Machine Learning Automation, Artificial Intelligence (AI), Deep Learning, Chatbots, AI Programming, Large Language Models (LLMs), OpenAI, LangChain, Image Generation, Generative Artificial Intelligence (GenAI), OpenAI GPT-3 API, Image Processing, QGIS, Remote Sensing, Videos, APIs, OpenAI GPT-4 API, Generative Pre-trained Transformers (GPT), Machine Learning Operations (MLOps), Recommendation Systems, Hugging Face, LoRa, Cloud Point, Axiom

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