
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 (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
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
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
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.
AI Developer
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.
AI Lead
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.
Lead Machine Learning Engineer
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.
Lead Machine Learning Engineer
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.
Machine Learning Engineer
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.
Experience
Automatic Product Tagging
Recommendation System
https://lackadaisical-olive-pumpkin.glitch.me/recommendation-systems-details.htmlComplete-the-look
https://lackadaisical-olive-pumpkin.glitch.me/complete-the-look-details.htmlRemote Sensing Applications for Geospatial Analysis
https://lackadaisical-olive-pumpkin.glitch.me/remote-sensing-applications-details.htmlMineral Alteration Mapping
https://lackadaisical-olive-pumpkin.glitch.me/mineral-alteration-mapping-details.htmlAs 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
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.htmlBy 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
PhD in Computer Engineering
University of Victoria - Victoria, BC, Canada
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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