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

Verified Expert  in Engineering

Bio

Belal is a senior machine learning (ML) engineer with over a decade of experience developing and deploying AI-driven systems. His work has spanned LLMs, multi-agent frameworks, classification, recommendation systems, and computer vision. He has been involved across the full ML lifecycle, including research, model development, deployment, and system optimization. Belal is experienced with technologies such as LangChain, LangGraph, GPT, LLama, AWS, NLP, and computer vision.

Portfolio

The Reynolds and Reynolds Company - Main
Machine Learning, Natural Language Processing (NLP), Python...
Jottix Inc.
Artificial Intelligence (AI), OpenAI, OpenAI o1, OpenAI GPT-4 API
Konner Frey
Artificial Intelligence (AI), Natural Language Processing (NLP)...

Experience

  • Model Tuning - 8 years
  • Prompt Engineering - 8 years
  • Machine Learning - 8 years
  • Python - 6 years
  • OpenAI - 3 years
  • Amazon Web Services (AWS) - 3 years
  • Natural Language Processing (NLP) - 3 years
  • DeepSeek - 1 year

Availability

Part-time

Preferred Environment

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

The most amazing...

...thing I built was a chatbot system based on LLMs, leveraging LangChain and GPT models to provide automated customer service in a human-like interaction.

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, DeepSeek, Agentic AI, Conversational AI, Retrieval-augmented Generation (RAG), OpenAI API, LangGraph, API Integration, System Architecture Design, Fine-tuning, Open-source LLMs, Agile, Scrum, Neural Networks

AI Developer

2024 - 2025
Jottix Inc.
  • Developed a multi-agent workflow powered by LLM to create a financial advisor. This system is capable of providing personalized financial planning based on customer profile data.
  • Created new tools to give the agents access to financial documentation to provide personalized financial planning.
  • Created another agent to send personalized financial planning via email.
Technologies: Artificial Intelligence (AI), OpenAI, OpenAI o1, OpenAI GPT-4 API

AI Lead

2024 - 2024
Konner Frey
  • Participated in the product discovery phase to address all product requirements.
  • Validated the idea by evaluating all challenges and bottlenecks the team could face during implementation.
  • Led the product road mapping to define all necessary tasks to complete the MVP.
Technologies: Artificial Intelligence (AI), Natural Language Processing (NLP), Machine Learning, Deep Learning, Computer Vision, Distributed Computing, Agile

Lead Machine Learning Engineer

2020 - 2023
XGen
  • 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 (CNNs), 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, Google Vision API, Fashion, API Integration, Agile, Scrum, Neural Networks

Lead Machine Learning Engineer

2020 - 2022
Niricson
  • 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 (CNNs), 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, API Integration, Agile, Scrum, Neural Networks

Machine Learning Engineer

2017 - 2020
PhotoSat
  • 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 (CNNs), Supervised Machine Learning, Machine Learning Automation, PyTorch, Artificial Intelligence (AI), OpenCV, Pandas, Deep Learning, AI Programming, Data Science, Image Generation, Image Processing, Remini, Agile, Scrum, Neural Networks

Experience

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

https://lackadaisical-olive-pumpkin.glitch.me/recommendation-systems-details.html
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.

Complete-the-look

https://lackadaisical-olive-pumpkin.glitch.me/complete-the-look-details.html
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

https://lackadaisical-olive-pumpkin.glitch.me/remote-sensing-applications-details.html
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

https://lackadaisical-olive-pumpkin.glitch.me/mineral-alteration-mapping-details.html
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

https://lackadaisical-olive-pumpkin.glitch.me/defects-mapping-details.html
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.

Education

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

Skills

Libraries/APIs

TensorFlow, Keras, PyTorch, OpenCV, Pandas, OpenAI API, Natural Language Toolkit (NLTK), SpaCy, Google Vision API

Tools

Slack, Zoom, ChatGPT, MATLAB, Remini, DeepSeek, OpenAI o1

Languages

Python

Frameworks

LangGraph

Paradigms

Agile, Scrum, Distributed Computing

Platforms

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

Storage

Data Pipelines, Google Cloud, Redis, MySQL, ClickHouse

Other

Machine Learning, Computer Vision, Research, Complex Problem Solving, CI/CD Pipelines, Natural Language Processing (NLP), Convolutional Neural Networks (CNNs), Supervised Machine Learning, Machine Learning Automation, Artificial Intelligence (AI), Deep Learning, Chatbots, AI Programming, Data Science, Large Language Models (LLMs), OpenAI, LangChain, Image Generation, Generative Artificial Intelligence (GenAI), OpenAI GPT-3 API, Image Processing, Prompt Engineering, Model Tuning, Agentic AI, Conversational AI, Retrieval-augmented Generation (RAG), Fashion, API Integration, Fine-tuning, Open-source LLMs, Neural Networks, 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, System Architecture Design, Axiom

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