Wassim is currently unavailable
Wassim Seifeddine
Verified Expert in Engineering
Machine Learning Developer
Paris, France
Toptal member since September 23, 2022
Bio
Wassim is a software engineer with 7+ years of experience, including 4+ years in machine learning. He worked with various clients, from startups to research institutes to multinational corporations, leveraging various technologies, including ChatGPT and DeepSeek. Wassim stands out from the crowd because he is thorough about building scalable solutions that are adaptive to business requirements.
Portfolio
Thomson Reuters
Machine Learning, Datasets, DeepSeek, Llama 3, Meta Llama, OpenAI GPT-4 API...
Self-employed
Biotechnology, PyTorch, Biology, Biotite, AlphaFold, ESM, EvolutionaryScale...
Establishment LAMAR AL-AWLA For Information Technology
Text-to-Speech (TTS), Artificial Intelligence (AI), Machine Learning...
Experience
- Natural Language Processing (NLP) - 9 years
- Artificial Intelligence (AI) - 9 years
- Machine Learning - 9 years
- Computer Vision - 6 years
- Optimization - 4 years
- Deep Learning - 4 years
- Generative Pre-trained Transformers (GPT) - 3 years
- DeepSeek - 1 year
Preferred Environment
PyTorch, PySpark, NumPy, Jupyter Notebook, Pandas, Amazon Web Services (AWS), Generative Pre-trained Transformers (GPT), Natural Language Processing (NLP), Computer Vision, Python, Artificial Intelligence (AI), GPU Computing
The most amazing...
...project I’ve built is a legal case classification model, a system that classifies case descriptions and highlights crucial text elements.
Work Experience
Senior Research Engineer
2025 - PRESENT
Thomson Reuters
- Conducted research on building better-specialized foundation models.
- Improved our LLM using data-centric techniques.
- Worked on reasoning models with post-training strategies.
Technologies: Machine Learning, Datasets, DeepSeek, Llama 3, Meta Llama, OpenAI GPT-4 API, Qwen
Senior Machine Learning Engineer
2023 - PRESENT
Self-employed
- Conducted research on biotech papers. I am specifically interested in genomics foundation models.
- Trained AlphaFold 3 custom implementation on a GPU cluster.
- Trained HyenaDNA with multiple attention mechanisms.
Technologies: Biotechnology, PyTorch, Biology, Biotite, AlphaFold, ESM, EvolutionaryScale, ESM3, Email Blasts
AI/ML Expert
2024 - 2025
Establishment LAMAR AL-AWLA For Information Technology
- Developed a speech foundation model that's trained on audio end-to-end.
- Devised a data set of specific languages and dialects for voice synthesis.
- Developed a test bench to evaluate the generation's quality of new models.
Technologies: Text-to-Speech (TTS), Artificial Intelligence (AI), Machine Learning, AI Model Training, Fine-tuning, Arabic
Senior Machine Learning Engineer
2023 - 2025
Aleksandar Zvorinji
- Developed large-scale speech foundation models to understand multilingual audio input.
- Trained the model on a custom multi-node cluster with more than 100 GPUs.
- Researched, experimented, and developed the model from scratch using the paper as a reference.
Technologies: Machine Learning, Artificial Intelligence (AI), Reinforcement Learning, Text-to-Speech (TTS), Speech Synthesis
AI Specialist Consultant
2024 - 2024
Mark Media - FZCO
- Conducted a comprehensive review of a GPT-4-powered real estate chatbot, providing detailed recommendations to enhance response quality, function calling strategies, and overall user experience.
- Evaluated the chatbot’s architecture and technical workflows, identifying key areas for optimization and ensuring compliance with data handling best practices.
- Delivered actionable feedback to refine the chatbot’s functionality, enabling efficient property information retrieval, improved conversational flow, and scalability for future feature expansions.
Technologies: Artificial Intelligence (AI), Chatbots, Generative Pre-trained Transformer 4 (GPT-4), Generative Pre-trained Transformers (GPT), Large Language Models (LLMs), DeepSeek
AI/LLM Consultant
2024 - 2024
Foundever - Main
- Developed a comprehensive strategy for LLM training factories.
- Designed data pipeline architecture using distributed computing.
- Collaborated with various technical teams to ensure smooth strategy operation.
Technologies: Large Language Models (LLMs), Python, Generative Artificial Intelligence (GenAI), Machine Learning, LoRa, Hugging Face, Natural Language Processing (NLP)
Reinforcement Learning Expert
2024 - 2024
Pocketbud Fintech (OPC) Pvt Ltd
- Researched the spaced repetition algorithm to implement a custom algorithm for the GRE/GMAT test.
- Built, trained, and finetuned a custom-spaced repetition system.
- Developed an end-to-end pipeline to consume GMAT error logs and process them into the spaced repetition schedule to ensure maximum efficiency of the reviews.
Technologies: Reinforcement Learning, Artificial Intelligence (AI), Education, Spaced Repetition
Image Processing Expert
2024 - 2024
Design Barn, Inc.
- Developed and refined algorithms for high-fidelity conversion of raster images to vector formats, leveraging AI and machine learning for process optimization.
- Implemented C++, Python, and JavaScript solutions, ensuring compatibility and performance across various platforms.
- Applied parallel programming techniques and GPU acceleration to improve processing speed and efficiency.
- Collaborated with UI/UX designers, front-end and back-end developers, and product managers to integrate conversion features seamlessly.
Technologies: Image Processing, Computer Vision, Python, C++, JavaScript, Linux Servers, Raster to Vector, GPU Computing, Parallel Computing, APIs, Artificial Intelligence (AI), Machine Learning, Amazon Web Services (AWS), Azure, Lottie
Machine Learning Engineer (via Toptal)
2024 - 2024
Safe Sign Technologies Limited
- Implemented custom loss functions for LLM fine-tuning.
- Implemented continued pre-training and instruction fine-tuning scripts for LLMs on multi-node clusters.
- Ensured dataset consistency and proper formatting of instruction tokens.
Technologies: Machine Learning, Large Language Models (LLMs), Fine-tuning, Together.ai, Distributed Cloud, PyTorch, AI Model Training, Instruction Tunning
Senior AI Engineer
2023 - 2024
ETH University - Zurich
- Developed a dynamic chatbot for a research experiment studying decision-making in teams of human and AI agents.
- Integrated the concept of "hidden profiles," enabling chat participants—both AI and human—to possess common and unique knowledge pieces to simulate different decision-making conditions.
- Integrated the chatbot into the Qualtrics platform using JavaScript, ensuring compatibility with existing code for seamless online interaction.
- Collaborated with the research lead to provide technical recommendations and document requirements, as well as deliver budget-conscious estimations.
Technologies: Artificial Intelligence (AI), Natural Language Processing (NLP), Python, JavaScript, Chatbots, OpenAI GPT-3 API, OpenAI GPT-4 API, Qualtrics
Machine Learning Engineer
2023 - 2024
Mawdoo3 Ltd
- Developed and optimized a fine-tuning pipeline for the LLAMA 2 model, enhancing its adaptability for diverse new domains and languages.
- Oversaw the development of the distributed training pipeline to run on GCP Vertex AI.
- Implemented comprehensive monitoring systems for training and inference.
Technologies: Artificial Intelligence (AI), Llama 2, Natural Language Processing (NLP), Google Cloud Platform (GCP), Machine Learning Operations (MLOps), Prompt Engineering, Retrieval-augmented Generation (RAG), Instruction Tunning, Technical Consulting
Machine Learning Engineer
2022 - 2024
Animaj
- Cultivated concept extraction from text, audio, and video content to understand social media trends better. Concepts include emotions, activities, and sentiments on what's going on in the video.
- Developed a set of Apache Airflow directed acyclic graphs (DAGs) to orchestrate data and machine learning (ML) pipelines.
- Created a monitoring system to have a bird's eye view of the whole system with outlier detection for out-of-distribution inputs/outputs.
- Fine-tuned LLMs (GPT-J, GPT-NeoX, and Llama) on new datasets using memory and time-efficient techniques like LoRA, DeepSpeed ZeRO, and PyTorch's FSDP.
- Worked on 2D/3D image and video generation models using Stable Diffusion and other generative AI models fine-tuned on a custom dataset.
- Showed experience (research and industry) in quantized models for more efficient training and inference.
- Worked on cutting-edge image models for segmentation and objection detection.
- Built a model that helps understand how videos are trending using unsupervised learning to cluster similar videos together.
- Implemented a YouTube ad optimization model for optimal placement of mid-roll ads.
Technologies: PyTorch, Data Lakes, Data Warehousing, Trend Forecasting, Topic Modeling, Revenue Projections, Video Analysis, Speech Synthesis, Sound, Text Animation, Diffusion Models, Image Generation, Databricks, Matplotlib, Predictive Modeling, PySpark, NumPy, Deep Neural Networks (DNNs), Data Engineering, AI Design, Forecasting, Data Visualization, Algorithms, Data Analytics, OpenAI, OpenCV, Computer Vision Algorithms, Language Models, Optical Character Recognition (OCR), Consulting, Startup Consulting, ETL, Apache Airflow, Data Analysis, Predictive Analytics, SQL, GPT Neo, Google Publisher Tag (GPT), Statistics, Python 3, Datasets, Causal Inference, Fine-tuning, Data Inference, Text Generation, Scikit-learn, Programming, Amazon Web Services (AWS), Speech Recognition, Architecture, Web Development, Snowflake, Analytics, AWS Lambda, NoSQL, Amazon EKS, Bash, Docker, MySQL, XGBoost, Large Language Models (LLMs), AWS ELB, Amazon Elastic Container Service (ECS), AWS Fargate, API Integration, Generative Pre-trained Transformer 4 (GPT-4), OpenAI GPT-3 API, Data Management, YouTube API, YouTube Ads, Videos, Optimization, Stable Diffusion, ControlNet, LoRa, Distributed Computing, Amazon DynamoDB, Apache Spark, Spark, Generative Pre-trained Transformer 3 (GPT-3), OpenAI GPT-4 API, Software Architecture, Graphics Processing Unit (GPU), Convolutional Neural Networks (CNNs), Image Analysis, Machine Learning Operations (MLOps), GPU Computing, Cloud Architecture, Models, Generative Artificial Intelligence (GenAI), Object Detection, JavaScript, Prompt Engineering, AI-generated Video
AI/ML Expert
2023 - 2023
Sneaky Panda Limited
- Developed a neural network to mimic real players in our game, serving as a tool for balancing the game's economy.
- Advised the client on architectural design and recommended subsequent steps to be taken.
- Created an AI model that simulates player behavior for the purpose of adjusting and optimizing the game's economic system.
Technologies: Reinforcement Learning, Deep Reinforcement Learning, AI Programming, Artificial Intelligence (AI), Machine Learning, Game Development, Mobile Games, DQN, Data, Instruction Tunning
PyTorch Deployment Specialist – Product Auditing
2023 - 2023
OctoML, Inc.
- Conducted a comprehensive audit of the AI platform, identifying key areas for performance enhancement and user experience improvements.
- Facilitated user experience improvements by highlighting areas for enhancing the new user experience, influencing a redesign that increased user engagement and satisfaction.
- Documented all audit findings and recommendations, offering a clear and actionable guide for platform enhancements.
Technologies: PyTorch, Python, Machine Learning, Instruction Tunning, Technical Consulting
NLP Engineer
2023 - 2023
Manada Technology LLC
- Acted as the AI advisor for building personalized GPT models on custom datasets.
- Helped optimize data ingestion and cleaning pipelines.
- Applied techniques from prompt engineering to improve the LLM generation quality.
- Assisted the development team in optimizing their development and experimentation process.
Technologies: Machine Learning, Artificial Intelligence (AI), Natural Language Processing (NLP), Large Language Models (LLMs), Data Engineering, Generative Pre-trained Transformers (GPT), Modeling, Fine-tuning, Meta Llama, MosaicML, OpenAI, OpenAI GPT-4 API, Prompt Engineering, Retrieval-augmented Generation (RAG), Instruction Tunning, Technical Consulting
NLP/Python Developer
2023 - 2023
Northeastern University - College of Engineering
- Worked on a tool to implement aspect-based sentiment analysis on product reviews.
- Developed a mechanism to summarize reviews based on aspects.
- Fine-tuned ML models on custom datasets to improve performance.
Technologies: Natural Language Processing (NLP), Machine Learning, Python, Amazon Web Services (AWS), APIs, JavaScript, Prompt Engineering, Retrieval-augmented Generation (RAG), Instruction Tunning
AI/ML Expert
2023 - 2023
1Bstories
- Developed a system to generate realistic-looking avatars based on multiple user choices to use with TTS models.
- Built a scene generation pipeline that generates images based on a specific description and preference.
- Deployed MLflow to production to monitor all ongoing machine learning model inferences.
Technologies: Artificial Intelligence (AI), Machine Learning, Stable Diffusion, Text to Image, Text to Video, MLflow, Midjourney, Avatars, Image Generation, Models, JavaScript, Prompt Engineering, Retrieval-augmented Generation (RAG), Instruction Tunning
AI/ML Specialist
2023 - 2023
Rich Lemon Apps FZE LLC
- Trained the AI model to generate user avatars in a specific style while preserving facial features.
- Achieved significant improvements compared to the previous approach using Dreambooth, resulting in avatars that closely resemble the original faces.
- Applied specific prompt formatting to improve the relevance of the generated avatars with the client's requirement.
- Utilized strong knowledge of AI/ML, Python, LoRA, diffusion models, stable diffusion, and image processing to accomplish project goals.
Technologies: Artificial Intelligence (AI), Machine Learning, Stable Diffusion, Image Processing, Fine-tuning, Python, ControlNet, LoRa, DreamBooth, Kohya, Convolutional Neural Networks (CNNs), Image Analysis, GPU Computing, Models, Prompt Engineering, Instruction Tunning
Machine Learning Engineer
2023 - 2023
Martian Learning Inc.
- Helped with debugging evaluation issues for custom deep learning model.
- Worked with a team of AI researchers to debug the performance of the model router.
- Ran the model on a GPU cluster for training and evaluation.
Technologies: Machine Learning, Artificial Intelligence (AI), Python, PyTorch, Distributed Computing, Machine Learning Operations (MLOps), GPU Computing, Models, Instruction Tunning
Machine Learning Engineer
2023 - 2023
Odem Global Pty Ltd
- Fine-tuned LLMs to deploy to a decentralized blockchain.
- Developed a gRPC server to offload inference to remote servers.
- Improved the inference speed of cutting-edge LLMs to deploy on more resource-constrained servers.
- Applied prompt engineering and network (data flow) analysis to ensure the LLMs generated the best possible responses among the top 1,024 competing models.
Technologies: Language Models, Machine Learning, Python, PyTorch, Fine-tuning, Causal Inference, Flash Attention, OpenAI GPT-3 API, APIs, Graphics Processing Unit (GPU), Convolutional Neural Networks (CNNs), Image Analysis, Machine Learning Operations (MLOps), GPU Computing, Cloud Architecture, Project Management, Models, JavaScript, Prompt Engineering, Retrieval-augmented Generation (RAG), Instruction Tunning
AI Developer
2023 - 2023
CodeComplete, Inc
- Engaged in the optimization of a causal language model's acceleration.
- Explored novel concepts to enhance performance by leveraging state-of-the-art technologies in the field.
- Conducted in-depth analysis and experimentation to identify potential bottlenecks and develop innovative solutions for optimizing the performance of the language model.
- Stayed abreast of the latest advancements in the field of language modeling and explored their applicability to improve further the acceleration and overall efficiency of the causal language model.
Technologies: C++, Machine Learning, Artificial Intelligence (AI), NVIDIA CUDA, PyTorch, cuBLAS, Flash Attention, gRPC, Generative Pre-trained Transformers (GPT), Generative Pre-trained Transformer 3 (GPT-3), Software Architecture, Graphics Processing Unit (GPU), Machine Learning Operations (MLOps), Cloud Architecture, Models, Prompt Engineering, Instruction Tunning, Technical Consulting
OCR AI Developer
2023 - 2023
ACFT PERFO
- Implemented a solution using AWS Textract to extract structured data from PDF files.
- Developed an end-to-end pipeline for extracting and saving the data into a data lake.
- Provided alternative solutions and tools to improve the efficiency and accuracy of the data extraction process.
Technologies: Amazon Textract, Amazon Web Services (AWS), Amazon SageMaker, Optical Character Recognition (OCR), Artificial Intelligence (AI), Python, Machine Learning, Amazon S3 (AWS S3), Python 3, Consulting, Software Architecture, Convolutional Neural Networks (CNNs), Image Analysis, Project Management, Models, JavaScript, Technical Consulting
Senior AI | Tech | HR Consultant
2023 - 2023
Block Born LLC
- Advised on AI tools to generate creative suggestions for game content production based on schema and scale.
- Reviewed and provided feedback on ideas related to implementing an AI tool for creative content suggestions.
- Demonstrated deep expertise in AI and its applications for creative content generation.
- Designed a specific prompt template to get the output of the LLM in the desired format that passes a validation pipeline.
Technologies: Artificial Intelligence (AI), Consulting, ChatGPT, Plugins, Generative Pre-trained Transformer 4 (GPT-4), APIs, OpenAI GPT-3 API, Stable Diffusion, ControlNet, Generative Pre-trained Transformer 3 (GPT-3), OpenAI GPT-4 API, Convolutional Neural Networks (CNNs), Image Analysis, Machine Learning Operations (MLOps), Cloud Architecture, Project Management, Models, JavaScript, Prompt Engineering, Technical Consulting
Machine Learning Engineer
2023 - 2023
Advest Marketing, LLC
- Worked on optimizing a product ads algorithm for social media.
- Researched techniques for improving product placement in videos.
- Explored deep learning techniques for generative modeling for videos.
Technologies: Machine Learning, Python, PyTorch, TensorFlow, Deep Learning, Diffusion Models, Generative Models, Graphics Processing Unit (GPU), Convolutional Neural Networks (CNNs), Image Analysis, Machine Learning Operations (MLOps), Cloud Architecture, Project Management, Models
Machine Learning Engineer
2022 - 2023
Toptal Client
- Trained a GPT-style model for simple language modeling to be deployed on a Bittensor network.
- Configured an iterative procedure to train models from previous checkpoints on new datasets.
- Monitored the model performance during and after training to know when to retrain.
Technologies: Machine Learning, Deep Learning, Python, Text Generation, Language Models, Blockchain, Natural Language Processing (NLP), Generative Pre-trained Transformers (GPT), Distributed Computing, Generative Pre-trained Transformer 3 (GPT-3), OpenAI GPT-4 API, Software Architecture, Graphics Processing Unit (GPU), Machine Learning Operations (MLOps), Cloud Architecture, Project Management, Models, Prompt Engineering, Instruction Tunning
Lead Machine Learning Engineer
2021 - 2023
Quantum Analytica
- Worked as a startup consultant for a real-estate startup to help them better understand their data infrastructure and guide them to the right tools using ETL pipelines, data lakes, delta tables, and hot storage.
- Developed a complete set of PySpark ETLs for transforming, cleaning, and normalizing data from different data sources and industries, including real estate and agriculture.
- Built a personalized ML-powered employee reward model as an MVP for an early-stage startup using customer-level data and rewards data from different providers.
- Managed the tech team, including designing the architecture for the whole team. The architecture ranges from web scrapers with dynamic proxies until the data is in hot storage, ready to be used by REST APIs.
- Developed machine learning models for consumer demand forecasters in the retail domain focusing on optimizing distribution to avoid out-of-stock.
- Worked on an algorithm for forecasting consumer demand for a certain set of products to help our client engage strategically in new markets.
- Developed an price outlier detection system for real estate ecommerce websites to notify users of potential good deals.
Technologies: PyTorch, ETL, PySpark, REST APIs, NumPy, Jupyter Notebook, Pandas, Machine Learning, Computer Vision, Python, Artificial Intelligence (AI), Recommendation Systems, Data Science, Image Processing, Advisory, Databricks, Deep Neural Networks (DNNs), Matplotlib, Data Engineering, AI Design, Forecasting, Data Visualization, APIs, Algorithms, Data Analytics, OpenAI, Predictive Modeling, OpenCV, Computer Vision Algorithms, Topic Modeling, Trend Forecasting, Data Warehousing, Data Lakes, Language Models, Optical Character Recognition (OCR), Data Scraping, Consulting, Technology Consulting, Slurm Workload Manager, Startup Consulting, Apache Airflow, Data Analysis, CTO, Predictive Analytics, SQL, GPT Neo, Google Publisher Tag (GPT), Statistics, Python 3, Datasets, DeepSpeed, Causal Inference, Fine-tuning, Data Inference, Text Generation, Scikit-learn, Programming, Amazon Web Services (AWS), Quantitative Finance, Speech Recognition, Architecture, Snowflake, Analytics, NoSQL, Amazon EKS, Bash, Docker, MySQL, XGBoost, Image Recognition, Handwriting Recognition, Large Language Models (LLMs), API Integration, Data Management, Distributed Computing, Amazon DynamoDB, Apache Spark, Spark, Data-driven Marketing, Pricing Models, Generative Pre-trained Transformer 3 (GPT-3), OpenAI GPT-4 API, Software Architecture, Graphics Processing Unit (GPU), Convolutional Neural Networks (CNNs), Image Analysis, Machine Learning Operations (MLOps), Cloud Architecture, Project Management, Models, JavaScript, Prompt Engineering, Instruction Tunning
PhD Researcher
2021 - 2022
Nantes Université
- Worked on my PhD thesis: The Acceleration of a Neural Network Using Computer Arithmetic.
- Devised new neural network training strategies to encourage better performances from low-precision neural networks.
- Developed custom CUDA operations for low-level operations and function approximations.
- Developed RL algorithm to solve optimization problems in large categorical observations spaces.
- Attended conferences and research schools related to machine learning and computer arithmetic.
Technologies: PyTorch, Arithmetic, Neural Networks, NumPy, Jupyter Notebook, Pandas, Machine Learning, Python, Artificial Intelligence (AI), C++, Data Science, Image Processing, Deep Neural Networks (DNNs), Matplotlib, AI Design, Algorithms, Internet of Things (IoT), Slurm Workload Manager, Data Analysis, Statistics, Python 3, Datasets, DeepSpeed, Causal Inference, Fine-tuning, Data Inference, Scikit-learn, Programming, Bash, NVIDIA CUDA, Docker, Image Recognition, Handwriting Recognition, Software Architecture, Graphics Processing Unit (GPU), Convolutional Neural Networks (CNNs), Image Analysis, Machine Learning Operations (MLOps), Project Management, Models
Researcher
2021 - 2021
Inria
- Worked on a research project to enable running big machine learning models on small resource-constrained devices using early exit networks.
- Collaborated with two professors to do a literature review on model compression techniques, including quantization, pruning, and knowledge distillation.
- Implemented a reinforcement learning solution (DQN) to solve an optimization problem.
- Published a paper for an international conference and presented the work at the meeting.
Technologies: PyTorch, Deep Neural Networks (DNNs), Microsoft Edge, NumPy, Jupyter Notebook, Pandas, Machine Learning, Computer Vision, Python, Artificial Intelligence (AI), C++, Data Science, Image Processing, Matplotlib, AI Design, Algorithms, OpenCV, Computer Vision Algorithms, Internet of Things (IoT), Slurm Workload Manager, Statistics, Python 3, Datasets, Causal Inference, Fine-tuning, Data Inference, Scikit-learn, Programming, Bash, Docker, API Integration, Graphics Processing Unit (GPU), Convolutional Neural Networks (CNNs), Image Analysis, Models
Machine Learning Engineer
2020 - 2020
Navya
- Made an object detection model faster and lighter to be able to run in pseudo real time to be deployed on a self-driving car.
- Worked closely with the core machine learning team in order to make sure we were aligned on the experiment setup and results.
- Experimented with multiple model compression strategies like pruning, quantization, and compiling to evaluate the efficacy of each method.
- Compressed the model around 4x with 3x improvement in inference speed while maintaining the same performance as the original model.
Technologies: PyTorch, Computer Vision, Object Detection, Quantization, NumPy, Jupyter Notebook, Pandas, Python, Artificial Intelligence (AI), Data Science, Image Processing, Advisory, Deep Neural Networks (DNNs), Matplotlib, AI Design, Data Visualization, APIs, Algorithms, Data Analytics, Predictive Modeling, OpenCV, Computer Vision Algorithms, Consulting, Predictive Analytics, Statistics, Python 3, Datasets, Causal Inference, Fine-tuning, Scikit-learn, Programming, Web Development, Analytics, Bash, Docker, MySQL, XGBoost, Object Tracking, Image Recognition, Handwriting Recognition, API Integration, Software Architecture, Graphics Processing Unit (GPU), Convolutional Neural Networks (CNNs), Image Analysis, Cloud Architecture, Project Management, Models
Data Scientist
2020 - 2020
SannSyn
- Developed a system that classifies legal cases from raw text input by an industry expert. The data given was raw scraped and OCR'd pdf from online sources.
- Performed data analysis of unstructured data to understand what could be done with the data and the needed processes to improve the quality.
- Built a web scraper to scrape financial news.
- Provided a sentiment analysis feature for financial news articles using transformer-based models.
Technologies: PyTorch, Sentiment Analysis, Text Classification, NumPy, Jupyter Notebook, Pandas, Machine Learning, Computer Vision, Python, Artificial Intelligence (AI), Data Science, Image Processing, PySpark, Deep Neural Networks (DNNs), Matplotlib, Data Visualization, APIs, Algorithms, Data Analytics, Predictive Modeling, OpenCV, Computer Vision Algorithms, Data Scraping, Predictive Analytics, SQL, Statistics, Python 3, Datasets, Fine-tuning, Data Inference, Scikit-learn, Programming, Amazon Web Services (AWS), NoSQL, Bash, Docker, MySQL, XGBoost, API Integration, Software Architecture, Machine Learning Operations (MLOps), Cloud Architecture, Project Management, Models
Machine Learning Engineer
2019 - 2019
Tedmob
- Developed a customer-facing chatbot using RASA AI, Dialogflow, and Microsoft bot framework for a leading telecom operator for handling FAQ and account-related questions with OTP authentication and third-party integrations.
- Tracked issues in real-time using various tools like Sentry, ELK stack, and Docker monitoring tools.
- Handled meeting with the client and gathered various team requirements for the best launch process.
Technologies: PyTorch, Machine Learning, Chatbots, Recommendation Systems, TensorFlow, PySpark, NumPy, Jupyter Notebook, Pandas, Computer Vision, Python, Artificial Intelligence (AI), Data Science, Image Processing, Advisory, Deep Neural Networks (DNNs), Matplotlib, Algorithms, OpenCV, Computer Vision Algorithms, Consulting, Technology Consulting, SQL, Statistics, Python 3, Datasets, Fine-tuning, Scikit-learn, Programming, Amazon Web Services (AWS), Speech Recognition, Web Development, NoSQL, Bash, Docker, API Integration, Amazon DynamoDB, Google Cloud Platform (GCP), Software Architecture, Convolutional Neural Networks (CNNs), Image Analysis, Machine Learning Operations (MLOps), Cloud Architecture, Project Management, Models, JavaScript, Medical Imaging
Head of the iOS Department
2017 - 2019
Tedmob
- Led and oversaw a team of iOS developers for two years.
- Managed the hiring and onboarding process for new hires.
- Migrated the team tech stack and incorporated a new software architecture.
Technologies: Swift, Jira, Xcode, Jupyter Notebook, Python, Algorithms, Technology Consulting, Programming, NoSQL, API Integration, App Development, Software Architecture, Cloud Architecture, Project Management
iOS Developer
2016 - 2017
Tedmob
- Developed commercial applications for clients ranging from one-person startups to multinational companies.
- Tracked issues happening on the application side in real time and resolved them in the next release.
- Migrated old applications from Objective-C to Swift.
Technologies: Swift, iOS, Xcode, Algorithms, Mobile Development, Mobile App Development, Programming, NoSQL, API Integration, App Development, Software Architecture, Project Management
Experience
Concept Extraction from Videos
A complete set of ML models to extract concepts from video data, including transcripts, audio tracks, thumbnails, and the actual video footage.
The concepts include:
• Emotions
• Activities
• Sentiment
• Objects
• Movement
The concepts include:
• Emotions
• Activities
• Sentiment
• Objects
• Movement
Quantized Neural Network for Object Detection
This work was done as part of a project with a self-driving car company where the aim was to take a pre-trained model and try to run it as fast as possible and as light as possible to be used for real-time object detection.
The model used is a MobileNetV2 pre-trained model on ImageNet with an SSDLite object detector. We trained the model in an FP32 data format.
I applied several model compression techniques to reduce the model's size and monitor its performance.
Some of the methods we used are:
• Quantization
• Pruning
• Fused convolution
• Knowledge distillation
The work concluded that the model could reliably detect objects in images with the same accuracy as the FP32 version while going as low as the INT8 data format.
The model used is a MobileNetV2 pre-trained model on ImageNet with an SSDLite object detector. We trained the model in an FP32 data format.
I applied several model compression techniques to reduce the model's size and monitor its performance.
Some of the methods we used are:
• Quantization
• Pruning
• Fused convolution
• Knowledge distillation
The work concluded that the model could reliably detect objects in images with the same accuracy as the FP32 version while going as low as the INT8 data format.
Casual Language Model Fine-tuning
Iteratively fine-tuned a GPT-like simple language model on a large dataset to be deployed on a blockchain network. The training procedure included using DeepSpeed for model parallelism and custom loggers for monitoring using the weights and biases service.
Legal Case Classification
This project was threefolds:
• EDA on unstructured messy text data to understand what can be done with the data
• Build a model that would classify a legal case based on the description entered into several categories. This part aimed to provide a tool to help lawyers classify cases faster and more easily.
• Extract the entities from the case description relevant to the classification to help counterarguments.
• EDA on unstructured messy text data to understand what can be done with the data
• Build a model that would classify a legal case based on the description entered into several categories. This part aimed to provide a tool to help lawyers classify cases faster and more easily.
• Extract the entities from the case description relevant to the classification to help counterarguments.
Custom Language Model Training Framework
https://github.com/pegesund/nor_bertA dataset agnostic training framework for transformer-based language models, and this project was to help bridge the performance gap between English and non-English language models. The final library should be integrated into the famous SentenceTransformer NLP package to be used directly.
Multi-modal Text Classifier
A machine learning model for extracting multiple labels from input streamed text data and I oversaw building this model end to end. The objective is to use the output of this model as a feature for another classifier.
Twitter Sentiment Analysis
A text classification model that classifies the sentiment of a single tweet or a hashtag on Twitter, where the model is a transformer-based BERT model fine-tuned on a sentiment analysis dataset. The model is hosted using Streamlit.
Running Neural Networks on Edge Devices
https://ieeexplore.ieee.org/abstract/document/9664700I developed a novel technique for successfully executing parts of a single model through multiple devices like IoT, edge, and cloud while respecting each device's resource limitations and for that, I introduced a new offloading mechanism where, during computation, a decision can be made to offload work, together with the ability to exit early in the computation with intermediate results, where the decision itself is tuned through deep Q-learning.
Norwegian Sentiment Analysis Model
A Transformer based neural network for classifying the sentiment of financial news into three main categories:
• Positive
• Neutral
• Negative.
The main difficulty was finding a good Norwegian labeled sentiment analysis dataset and fine-tuning an existing multilingual model.
• Positive
• Neutral
• Negative.
The main difficulty was finding a good Norwegian labeled sentiment analysis dataset and fine-tuning an existing multilingual model.
Education
2021 - 2022
PhD in Computer Science
Nantes Université - Nantes, France
2019 - 2021
Master's Degree in Artificial Intelligence
ESIEE Paris - Paris, France
2014 - 2018
Bachelor's Degree in Computer Science
Lebanese University - Beirut, Lebanon
Certifications
MARCH 2020 - PRESENT
Deep Learning Specialization
DeepLearning.ai | via Coursera
MAY 2019 - PRESENT
Advanced Machine Learning Specialization
DeepLearning.AI and Stanford Online | via Coursera
MAY 2018 - PRESENT
Machine Learning
Stanford University | via Coursera
JULY 2016 - PRESENT
iOS Developer Nanodegree
Udacity
Skills
Libraries/APIs
PyTorch, NumPy, Pandas, Matplotlib, XGBoost, PySpark, TensorFlow, OpenCV, DeepSpeed, REST APIs, Scikit-learn, YouTube API, cuBLAS
Tools
Apache Airflow, Amazon EKS, Google Bard, Xcode, Jira, Jupyter, AWS ELB, Amazon Elastic Container Service (ECS), AWS Fargate, ChatGPT, Amazon Textract, Amazon SageMaker, Apache Iceberg, Qualtrics, DeepSeek
Languages
Python, Python 3, Bash, SQL, Snowflake, C++, Swift, JavaScript, Arabic
Paradigms
Mobile Development, ETL, App Development, Distributed Computing, Real-time Systems, Parallel Computing
Platforms
Jupyter Notebook, Docker, Databricks, Amazon Web Services (AWS), Embedded Linux, iOS, AWS Lambda, NVIDIA CUDA, Blockchain, Microsoft Edge, Google Cloud Platform (GCP), Kohya, MosaicML, Together.ai, Azure
Storage
NoSQL, MySQL, Amazon DynamoDB, Data Lakes, Amazon S3 (AWS S3)
Frameworks
Apache Spark, Spark, Flask, gRPC
Industry Expertise
Project Management
Other
Machine Learning, Computer Vision, Sentiment Analysis, Deep Learning, Natural Language Processing (NLP), Artificial Intelligence (AI), Data Science, Image Processing, Optical Character Recognition (OCR), Computer Vision Algorithms, Mobile App Development, Predictive Modeling, Algorithms, APIs, Data Analytics, Data Visualization, Forecasting, AI Design, Data Engineering, Deep Neural Networks (DNNs), Data Analysis, CTO, Predictive Analytics, Statistics, Datasets, Causal Inference, Fine-tuning, Data Inference, Programming, Architecture, Analytics, Image Recognition, API Integration, Generative Pre-trained Transformers (GPT), Software Architecture, Graphics Processing Unit (GPU), Convolutional Neural Networks (CNNs), Image Analysis, GPU Computing, Cloud Architecture, Models, Supervised Learning, Instruction Tunning, Technical Consulting, Text-to-Speech (TTS), Optimization, Consulting, Advisory, Technology Consulting, Startup Consulting, Facial Recognition, OpenAI, GPT Neo, Google Publisher Tag (GPT), Text Generation, Speech Recognition, Web Development, Handwriting Recognition, Large Language Models (LLMs), Data Management, Stable Diffusion, ControlNet, Machine Learning Operations (MLOps), Data-driven Marketing, Generative Pre-trained Transformer 3 (GPT-3), OpenAI GPT-4 API, Research, Outlier Detection, Unsupervised Learning, Prompt Engineering, Retrieval-augmented Generation (RAG), Medical Imaging, Technical Leadership, Vector Databases, LangChain, AI Agents, Graph Theory, Arithmetic, Object Detection, Neural Networks, Slurm Workload Manager, Chatbots, Recommendation Systems, Quantization, Data Scraping, Clustering, Text Classification, Internet of Things (IoT), Language Models, Data Warehousing, Trend Forecasting, Topic Modeling, Revenue Projections, Video Analysis, Speech Synthesis, Sound, Text Animation, Diffusion Models, Image Generation, Quantitative Finance, Object Tracking, Generative Models, Plugins, Generative Pre-trained Transformer 4 (GPT-4), OpenAI GPT-3 API, YouTube Ads, Videos, LoRa, Flash Attention, Pricing Models, DreamBooth, Wearables, Biometrics, Reinforcement Learning, Text to Image, Text to Video, MLflow, Midjourney, Avatars, DQN, Modeling, Meta Llama, Deep Reinforcement Learning, AI Programming, Game Development, Mobile Games, Data, Generative Artificial Intelligence (GenAI), Llama 2, Lottie, AI-generated Video, Distributed Cloud, AI Model Training, Linux Servers, Raster to Vector, Biotechnology, Biology, Biotite, AlphaFold, ESM, EvolutionaryScale, ESM3, Education, Spaced Repetition, Email Blasts, Hugging Face, Llama 3, Qwen, Cloud
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