Fuad Issa, Machine Learning Developer in London, United Kingdom
Fuad Issa

Machine Learning Developer in London, United Kingdom

Member since July 22, 2022
Fuad is an experienced machine learning engineer and data scientist with a background in building major, scalable production systems for information extraction and knowledge base population. He enjoys designing and creating a state of art solutions for custom NLP problems. Fuad is proficient in recent advances and models to build semantic search systems, information extraction, and recommender systems utilizing NLU technologies.
Fuad is now available for hire

Portfolio

  • Springbok
    Python 3, Rasa NLU, GPT3, PyTorch, TensorFlow, APIs, Microservices...
  • ComplyAdvantage
    Python 3, AWS, Kubernetes, Docker, Helm, CI/CD Pipelines...

Experience

  • Natural Language Understanding (NLU) 6 years
  • Python 3 6 years
  • Computational Linguistics 6 years
  • TensorFlow 6 years
  • Machine Learning 6 years
  • PyTorch 4 years
  • Social Network Analysis 1 year
  • Recommendation Systems 1 year

Location

London, United Kingdom

Availability

Part-time

Preferred Environment

PyCharm, Python 3, Docker, Kubernetes, 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.

Employment

  • 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, GPT3, 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, AWS, Flask, Chatbots, Linux, MacOS, PyCharm, Mathematics, Statistics, Programming, Computational Linguistics, Natural Language Processing (NLP), Machine Learning Operations (MLOps), Continuous Delivery (CD), Continuous Integration (CI), Software Engineering, NumPy, Data Reporting, SciPy, Jupyter Notebook, Matplotlib, NLTK, Convolutional Neural Networks, Long Short-term Memory (LSTM), Applied Research, Supervised Machine Learning, Git, Topic Modeling, Python, SQL, NoSQL, Deep Learning, Neural Networks, Code Review, Task Analysis
  • 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, AWS, Kubernetes, Docker, Helm, CI/CD Pipelines, Natural Language Understanding (NLU), Natural Language Processing (NLP), 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, NLTK, Convolutional Neural Networks, 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

Experience

  • 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.

  • 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.

Skills

  • Languages

    Python 3, Python, SQL
  • Frameworks

    Flask
  • Libraries/APIs

    PyTorch, TensorFlow, Keras, Pandas, NetworkX, Scikit-learn, NumPy, SciPy, Matplotlib, NLTK, REST APIs, Rasa NLU, MTurk API
  • Tools

    Git, Jupyter, PyCharm, Amazon SageMaker, Helm, GitLab, GitLab CI/CD
  • Paradigms

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

    Jupyter Notebook, Linux, MacOS, Docker, Kubernetes
  • Other

    Research, Programming, Natural Language Understanding (NLU), Machine Learning, Computational Linguistics, Natural Language Processing (NLP), GPT3, Recommendation Systems, NLU, Annotations, AMR, Software Engineering, Artificial Intelligence (AI), Data Reporting, Convolutional Neural Networks, 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, AWS, Mathematics, Statistics, Physics, Machine Vision, Social Network Analysis, Bayesian Inference & Modeling, Machine Learning Operations (MLOps), APIs, Big Data, Interviewing, Team Management, Computational Physics, Reinforcement Learning, Graph Theory, CI/CD Pipelines
  • Storage

    Elasticsearch, PostgreSQL, Amazon S3 (AWS S3), NoSQL

Education

  • Master's Degree in Artificial Intelligence
    2015 - 2016
    The University of Edinburgh - Edinburgh, UK
  • Master's Degree in Physics and Nanotechnology
    2014 - 2015
    The University of Cambridge - Cambridge, UK
  • Bachelor's Degree in Physics and Nanotechnology
    2009 - 2012
    The University of Leeds - Leeds, UK

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