Wassim is available for hire
Hire WassimWassim Seifeddine
Verified Expert in Engineering
Machine Learning Developer
Location
Paris, France
Toptal Member Since
September 23, 2022
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. Wassim stands out from the crowd because he is thorough about building scalable solutions that are adaptive to business requirements.
Portfolio
Animaj
PyTorch, Data Lakes, Data Warehousing, Trend Forecasting, Topic Modeling...
Manada Technology LLC
Machine Learning, Artificial Intelligence (AI)...
Northeastern University - College of Engineering
Natural Language Processing (NLP), Machine Learning, Python...
Experience
Availability
Part-time
Preferred Environment
PyTorch, PySpark, NumPy, Jupyter Notebook, Pandas, Amazon Web Services (AWS), GPT, 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
Machine Learning Engineer
2022 - PRESENT
Animaj
- Cultivated a 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.
- Finetuned LLMS (gptj, gpt-neox, llama) on new datasets using memory and time-efficient techniques like LoRA, DeepSpeed ZeRO, and PyTorch's FSDP.
- Generated 2D/3D images and videos using Stable Diffusion and other generative AI models finetuned on a custom dataset.
- Experienced (research and industry) on quantized models for more efficient training and inference.
- Deployed LLMs on decentralized networks with gRPC servers and mesh networks.
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, Data Engineering, AI Design, Forecasting, Data Visualization, Algorithms, Data Analytics, OpenAI, OpenCV, Computer Vision Algorithms, Language Models, 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 (Amazon ECS), AWS Fargate, API Integration, GPT-4, OpenAI GPT-3 API, Data Management, YouTube API, YouTube Ads, Optimization, Videos, 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, Image Analysis, Machine Learning Operations (MLOps), GPU Computing, Cloud Architecture, Models
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.
- 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, LLaMA, MosaicML, OpenAI, OpenAI GPT-4 API
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.
- Finetuned ML models on custom datasets to improve performance.
Technologies: Natural Language Processing (NLP), Machine Learning, Python, Amazon Web Services (AWS), APIs
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
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.
- 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, Image Analysis, GPU Computing, Models
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.
- Run 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
Machine Learning Engineer
2023 - 2023
Odem Global Pty Ltd
- Finetuned 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.
Technologies: Language Models, Machine Learning, Python, PyTorch, Fine-tuning, Causal Inference, Flash Attention, APIs, OpenAI GPT-3 API, Graphics Processing Unit (GPU), Convolutional Neural Networks, Image Analysis, Machine Learning Operations (MLOps), GPU Computing, Cloud Architecture, Project Management, Models
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
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, OCR, Artificial Intelligence (AI), Python, Machine Learning, Amazon S3 (AWS S3), Python 3, Consulting, Software Architecture, Convolutional Neural Networks, Image Analysis, Project Management, Models
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.
Technologies: Artificial Intelligence (AI), Consulting, ChatGPT, Plugins, GPT-4, APIs, OpenAI GPT-3 API, Stable Diffusion, ControlNet, Generative Pre-trained Transformer 3 (GPT-3), OpenAI GPT-4 API, Convolutional Neural Networks, Image Analysis, Machine Learning Operations (MLOps), Cloud Architecture, Project Management, Models
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, Image Analysis, Machine Learning Operations (MLOps), Cloud Architecture, Project Management, Models
ML Engineer with Skills in GPT-2/3
2022 - 2023
Toptal
- Trained a GPT-style model for simple language modeling to be deployed on a bit tensor 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, Generative Pre-trained Transformers (GPT), GPT, Natural Language Processing (NLP), 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
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.
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, 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, 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, Image Analysis, Machine Learning Operations (MLOps), Cloud Architecture, Project Management, Models
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, 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, 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, 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, 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, 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, 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, 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, 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, Image Analysis, Machine Learning Operations (MLOps), Cloud Architecture, Project Management, Models
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.
Skills
Languages
Python, Python 3, Bash, SQL, Snowflake, C++, Swift
Libraries/APIs
PyTorch, NumPy, Pandas, Matplotlib, XGBoost, PySpark, TensorFlow, OpenCV, REST APIs, Scikit-learn, YouTube API, cuBLAS
Paradigms
Data Science, Mobile Development, ETL, App Development, Distributed Computing, Real-time Systems
Platforms
Jupyter Notebook, Docker, Databricks, Amazon Web Services (AWS), Embedded Linux, iOS, AWS Lambda, NVIDIA CUDA, Blockchain, Microsoft Edge, Google Cloud Platform (GCP)
Storage
NoSQL, MySQL, Amazon DynamoDB, Data Lakes, Amazon S3 (AWS S3)
Other
Machine Learning, Computer Vision, Sentiment Analysis, Deep Learning, Natural Language Processing (NLP), Artificial Intelligence (AI), Image Processing, OCR, Computer Vision Algorithms, Mobile App Development, Predictive Modeling, Algorithms, APIs, Data Analytics, Data Visualization, Forecasting, AI Design, Data Engineering, Deep Neural Networks, Data Analysis, CTO, Predictive Analytics, Statistics, Datasets, Causal Inference, Fine-tuning, Data Inference, Programming, Architecture, Analytics, Image Recognition, API Integration, GPT, Generative Pre-trained Transformers (GPT), Software Architecture, Graphics Processing Unit (GPU), Convolutional Neural Networks, Image Analysis, GPU Computing, Cloud Architecture, Models, Optimization, Consulting, Advisory, Technology Consulting, Startup Consulting, Facial Recognition, OpenAI, GPT-Neo, Google Publisher Tag (GPT), DeepSpeed, 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, 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, ChatGPT, Plugins, GPT-4, OpenAI GPT-3 API, Amazon Textract, YouTube Ads, Videos, LoRa, Flash Attention, Pricing Models, DreamBooth, Kohya, Wearables, Biometrics, Reinforcement Learning, Text to Image, Text to Video, MLflow, Midjourney, Avatars, DQN, Modeling, LLaMA, MosaicML
Frameworks
Apache Spark, Spark, Flask, gRPC
Tools
Amazon EKS, Xcode, Jira, Jupyter, Apache Airflow, AWS ELB, Amazon Elastic Container Service (Amazon ECS), AWS Fargate, Amazon SageMaker
Industry Expertise
Project Management
Education
2021 - 2022
PhD Degree 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