Fuad Issa, Developer in London, United Kingdom
Fuad is available for hire
Hire Fuad

Fuad Issa

Verified Expert  in Engineering

Machine Learning Developer

Location
London, United Kingdom
Toptal Member Since
July 22, 2022

Fuad excels in building machine learning services from prototype to production, leveraging his diverse ML experience to craft rapid prototypes and discover creative uses for models across many domains. With a solid foundation in maths and programming, he stays at the forefront of the latest research, continually enhancing the solutions he provides to clients. Fuad's passion for developing cutting-edge technology solutions makes him a valuable asset to any team seeking to harness the power of ML.

Portfolio

Safesign Technologies
Machine Learning, Deep Learning, Large Language Models (LLMs), OpenAI
U15 - GROUP OF CANADIAN RESEARCH UNIVERSITIES
Data Science, Classification, Python, Text Classification, Data Pipelines...
Idesigns
Amazon S3 (AWS S3), Amazon Web Services (AWS), OpenAI GPT-4 API, Text to Image...

Experience

Availability

Part-time

Preferred Environment

PyCharm, Python 3, Docker, Kubernetes, Amazon Web Services (AWS), Jupyter Notebook, Git, GitLab, GitLab CI/CD

The most amazing...

...thing I've developed is an information extraction pipeline processing millions of articles to populate a knowledge graph.

Work Experience

Principal Research Engineer

2023 - PRESENT
Safesign Technologies
  • Led the development of a legal foundation model, as the principal research engineer.
  • Applied the latest cutting-edge research to create a system based on open source models that beat GPT-3.5 on the LegalBench benchmark.
  • Oversaw the growth of the team and selected top ML talent.
Technologies: Machine Learning, Deep Learning, Large Language Models (LLMs), OpenAI

Data Science Consultant

2023 - PRESENT
U15 - GROUP OF CANADIAN RESEARCH UNIVERSITIES
  • Created a cutting-edge Entity Linking system using RAG retrieval and LLMs to consolidate multiple data sources of university research into one.
  • Consulted the client on various AI technologies best suited to improve the product.
  • Prototyped an efficient document topic tagging system that can tag millions of documents.
Technologies: Data Science, Classification, Python, Text Classification, Data Pipelines, Amazon Web Services (AWS), AWS Fargate, Graphs, ETL, Machine Learning, Language Models, Generative Pre-trained Transformers (GPT), Technical Leadership, Mentorship & Coaching, OpenAI

Founder

2023 - PRESENT
Idesigns
  • Created a platform that allows the people to create designs inspired by their topic of interest, print it on product and get it delivered to their doorstep.
  • Moved from idea inception to building the back end and supervising freelancers to build the front end.
  • Integrated the app with various services such as Open AI API, text-to-image models on Stable Diffusion, Printify, and Shopify.
Technologies: Amazon S3 (AWS S3), Amazon Web Services (AWS), OpenAI GPT-4 API, Text to Image, Stable Diffusion, AWS Fargate, Hugging Face, Frameworks, LangChain, Pinecone, AI Design, AI Art Visualization, Technical Leadership, Leadership, Mentorship & Coaching, OpenAI

Chatbot Consultant

2023 - 2023
California State University , Long Beach
  • Designed and implemented an educational chatbot system.
  • Optimized the chatbot flow to respond to questions, run SQL queries, and suggest improvements.
  • Worked with the client to improve the chatbot's design to fit the needs of the educational system best.
Technologies: Python, AWS Lambda, Python 3, Amazon Lex, Amazon Web Services (AWS), OpenAI GPT-3 API, Chatbots, Technical Leadership, OpenAI

Machine Learning Consultant

2023 - 2023
Piggyback Inc
  • Created custom flows for Chatbot LLM model and retrieval system for more precise and accurate responses.
  • Consulted on the long-term AI strategy of the company.
  • Reduced hallucinations of the LLM model through various standard and bespoke methods.
Technologies: Artificial Intelligence (AI), OpenAI GPT-4 API, Machine Learning, OpenAI

Lead Data Scientist

2022 - 2023
Koble
  • Created a model to guide VC startup investment decisions. The model was a custom transformer network that takes in text and tabular features to predict the success probability of a startup given market, team, and funding features.
  • Created an NLP service that classifies companies according to a taxonomy of sectors.
  • Developed an NLP service that describes any company activity and products given their raw website.
  • Introduced good data science practices and processes to the team.
Technologies: Amazon S3 (AWS S3), APIs, REST, Kubernetes, AWS Lambda, Amazon SageMaker, Elasticsearch, BERT, Large Language Models (LLMs), Sentiment Analysis, Text Classification, Data Analysis, Language Learning, Language Models, Software as a Service (SaaS), OpenAI GPT-3 API, Artificial General Intelligence (AGI), Databases, Finance, Analytics, Machine Learning, Natural Language Processing (NLP), OpenAI GPT-4 API, MySQL, Statistical Data Analysis, Mathematical Analysis, Statistical Methods, Predictive Modeling, Data Scientist, Decision Trees, Regression, Consulting, Algorithms, ChatGPT, OpenAI Gym, Explainable Artificial Intelligence (XAI), Recurrent Neural Networks (RNNs), PDF Scraping, Scraping, Stable Diffusion, Text to Video, Text to Image, Artificial Intelligence (AI), Minimum Viable Product (MVP), Graphs, Data Pipelines, Classification, Hugging Face, Technical Leadership, Leadership, Mentorship & Coaching, OpenAI

Machine Learning Consultant

2022 - 2022
Telescope
  • Developed an automated email writing service based on historical emails and generative AI.
  • Created a recommender system that suggests people contact based on previous people searched, keywords, and company description.
  • Built an email classification system that classifies emails based on the type, e.g., sales, inquiry, follow-up, and more.
Technologies: Amazon Web Services (AWS), Amazon S3 (AWS S3), AWS Lambda, Elasticsearch, Recommendation Systems, BERT, Sentiment Analysis, Computational Linguistics, Large Language Models (LLMs), Text Classification, Data Analysis, Language Learning, Language Models, Software as a Service (SaaS), OpenAI GPT-3 API, Artificial General Intelligence (AGI), Databases, Machine Learning, Natural Language Processing (NLP), OpenAI GPT-4 API, MySQL, Mathematical Analysis, Statistical Methods, Predictive Modeling, Data Scientist, Decision Trees, Regression, Consulting, Algorithms, Explainable Artificial Intelligence (XAI), Recurrent Neural Networks (RNNs), Scraping, Minimum Viable Product (MVP), Classification, Hugging Face

Machine Learning Consultant

2020 - 2022
Springbok
  • Developed a system using GPT-3 to automatically create questions and answers from documents, feeding them to a chatbot system answering customers' queries.
  • Created a microservice for the linguistically aware natural language understanding (NLU) model to recommend text style correction for technical requirements.
  • Produced machine learning (ML) services for multiple natural language processing (NLP) tasks, including text classification and recommendation.
Technologies: Python 3, Rasa NLU, Generative Pre-trained Transformer 3 (GPT-3), PyTorch, TensorFlow, APIs, Microservices, Recommendation Systems, Natural Language Understanding (NLU), NLU, PostgreSQL, Amazon S3 (AWS S3), Artificial Intelligence (AI), Docker, Kubernetes, Machine Learning, Data Science, Jupyter, REST APIs, Annotations, Amazon Web Services (AWS), Flask, Chatbots, Linux, MacOS, PyCharm, Mathematics, Statistics, Programming, Computational Linguistics, Natural Language Processing (NLP), Generative Pre-trained Transformers (GPT), Machine Learning Operations (MLOps), Continuous Delivery (CD), Continuous Integration (CI), Software Engineering, NumPy, Data Reporting, SciPy, Jupyter Notebook, Matplotlib, Natural Language Toolkit (NLTK), Convolutional Neural Networks (CNN), Long Short-term Memory (LSTM), Applied Research, Supervised Machine Learning, Git, Topic Modeling, Python, SQL, NoSQL, Deep Learning, Neural Networks, Code Review, Task Analysis, Large Language Models (LLMs), Sentiment Analysis, Text Classification, Data Analysis, Language Learning, Language Models, Software as a Service (SaaS), OpenAI GPT-3 API, Databases, Analytics, OpenAI GPT-4 API, MySQL, Predictive Modeling, Data Scientist, Decision Trees, Regression, Consulting, Algorithms, Conversational Interfaces, Explainable Artificial Intelligence (XAI), Recurrent Neural Networks (RNNs), Scraping, Minimum Viable Product (MVP), Classification, Hugging Face

Senior Machine Learning Engineer

2016 - 2020
ComplyAdvantage
  • Built the ML pipeline models to read articles, an information extraction system that feeds into a knowledge graph of criminal and adverse media entities.
  • Improved the company's entity extraction and classification system eight times, increasing unique entities in the knowledge graph through implementing the latest NLU research.
  • Enhanced the ease of ML model deployment and development by redesigning the monolithic ML pipeline into a microservices-based scalable one.
  • Guided the team's growth by helping with research and development projects and managed a junior ML engineer.
  • Drove the inclusion of the latest NLP research in the company's solutions.
  • Built the ML pipelines and led data collection automation through MLOps practices.
  • Introduced an additional entity meta-data for the company's extraction system by developing a relation extractor using distant supervision methods.
  • Led a significant refactoring project following a microservices approach to split the company's main article-reading ML pipeline into multiple projects, using Elasticsearch, Kubernetes, Docker, AWS, and CI/CD.
Technologies: Python 3, Amazon Web Services (AWS), Kubernetes, Docker, Helm, CI/CD Pipelines, Natural Language Understanding (NLU), Natural Language Processing (NLP), Generative Pre-trained Transformers (GPT), Machine Learning, Machine Learning Operations (MLOps), ETL, TensorFlow, Keras, PyTorch, Pandas, NLU, Amazon SageMaker, MTurk API, Annotations, Amazon S3 (AWS S3), Continuous Delivery (CD), Continuous Integration (CI), Big Data, Software Engineering, Flask, APIs, Artificial Intelligence (AI), Data Science, NumPy, Data Reporting, Scikit-learn, SciPy, Jupyter Notebook, Matplotlib, Natural Language Toolkit (NLTK), Convolutional Neural Networks (CNN), Long Short-term Memory (LSTM), Applied Research, Supervised Machine Learning, Git, SQL, Topic Modeling, Linux, MacOS, PyCharm, Mathematics, Statistics, Programming, Social Network Analysis, Computational Linguistics, Rasa NLU, Microservices, PostgreSQL, Jupyter, REST APIs, Python, NoSQL, Deep Learning, Data Analytics, Neural Networks, Technical Hiring, Source Code Review, Code Review, Task Analysis, Interviewing, Team Management, Sentiment Analysis, Text Classification, Data Analysis, Know Your Customer (KYC), Risk Analysis, Software as a Service (SaaS), Databases, Finance, Analytics, Statistical Data Analysis, Mathematical Analysis, Statistical Methods, Predictive Modeling, Data Scientist, Decision Trees, Regression, Algorithms, Explainable Artificial Intelligence (XAI), Recurrent Neural Networks (RNNs), Scraping, Minimum Viable Product (MVP), Graphs, Data Pipelines, Classification, Hugging Face, Technical Leadership, Leadership, Mentorship & Coaching

Creative Design Work for a Platform

http://www.idesigns.shop
Built a platform that helps a user to create creative, funny designs with the help of generative text and image AI. The user can then select a product to print the design on and get it delivered to their doorstep.

Startup Success Predictor

Built a pipeline for a startup success classification model. The model takes in various data types, like tabular data and textual descriptions of the founders and the company. I built the data processing pipeline to handle serving and training time. Also, performed parallel training using Ray and built multiple smaller models like a company description generator. The model performs three times better than the average human random choice.

Article Reading System

This project was about an ML pipeline extracting names of people, companies, and sentence relations from millions of article texts to classify them according to a custom taxonomy.

The tasks involved building the models, dataset creation and collection, and data engineering to create the pipeline.

Abstract Meaning Representation for Paraphrase Detection

https://aclanthology.org/N18-1041/
Master's thesis results published in NAACL 2018. The thesis established that the graph representation of a sentence obtained using Abstract Meaning Representation (AMR) parsers is useful for detecting paraphrases. Achieved state-of-the-art results at the time using a novel PageRank enhanced reweighing method.
2015 - 2016

Master's Degree in Artificial Intelligence

The University of Edinburgh - Edinburgh, UK

2014 - 2015

Master's Degree in Physics and Nanotechnology

The University of Cambridge - Cambridge, UK

2009 - 2012

Bachelor's Degree in Physics and Nanotechnology

The University of Leeds - Leeds, UK

Libraries/APIs

PyTorch, TensorFlow, Keras, Pandas, NetworkX, Scikit-learn, NumPy, SciPy, Matplotlib, Natural Language Toolkit (NLTK), REST APIs, Rasa NLU, MTurk API

Tools

Amazon SageMaker, Git, Jupyter, ChatGPT, PyCharm, AWS Fargate, Helm, GitLab, GitLab CI/CD, OpenAI Gym, Amazon Lex

Frameworks

Flask

Languages

Python 3, Python, SQL

Paradigms

Continuous Delivery (CD), Continuous Integration (CI), Data Science, ETL, Microservices, REST

Platforms

Jupyter Notebook, Linux, MacOS, Amazon Web Services (AWS), Docker, Kubernetes, AWS Lambda

Storage

Databases, Elasticsearch, PostgreSQL, Amazon S3 (AWS S3), NoSQL, MySQL, Data Pipelines

Other

Research, Programming, Natural Language Understanding (NLU), Machine Learning, Computational Linguistics, Natural Language Processing (NLP), Generative Pre-trained Transformer 3 (GPT-3), Recommendation Systems, NLU, Annotations, AMR, Software Engineering, Artificial Intelligence (AI), Data Reporting, Convolutional Neural Networks (CNN), Long Short-term Memory (LSTM), Applied Research, Supervised Machine Learning, Topic Modeling, Chatbots, Deep Learning, Data Analytics, Neural Networks, Technical Hiring, Source Code Review, Code Review, Task Analysis, BERT, Sentiment Analysis, Large Language Models (LLMs), Text Classification, Google Colaboratory (Colab), Data Analysis, Generative Pre-trained Transformers (GPT), Language Models, Know Your Customer (KYC), Software as a Service (SaaS), OpenAI GPT-3 API, Analytics, OpenAI GPT-4 API, Mathematical Analysis, Statistical Methods, Predictive Modeling, Data Scientist, Decision Trees, Regression, Consulting, Explainable Artificial Intelligence (XAI), Recurrent Neural Networks (RNNs), Minimum Viable Product (MVP), Classification, Hugging Face, Technical Leadership, Leadership, Mentorship & Coaching, OpenAI, Mathematics, Statistics, Physics, Machine Vision, Social Network Analysis, Bayesian Inference & Modeling, Machine Learning Operations (MLOps), APIs, Big Data, Interviewing, Team Management, Language Learning, Risk Analysis, Artificial General Intelligence (AGI), Finance, Statistical Data Analysis, Algorithms, Conversational Interfaces, PDF Scraping, Scraping, Stable Diffusion, Text to Image, Graphs, Frameworks, LangChain, Pinecone, Computational Physics, Reinforcement Learning, Graph Theory, CI/CD Pipelines, Deep Neural Networks, Text to Video, AI Design, AI Art Visualization

Collaboration That Works

How to Work with Toptal

Toptal matches you directly with global industry experts from our network in hours—not weeks or months.

1

Share your needs

Discuss your requirements and refine your scope in a call with a Toptal domain expert.
2

Choose your talent

Get a short list of expertly matched talent within 24 hours to review, interview, and choose from.
3

Start your risk-free talent trial

Work with your chosen talent on a trial basis for up to two weeks. Pay only if you decide to hire them.

Top talent is in high demand.

Start hiring