Freelancer profile translated to English.

Description

Machine learning and IoT engineer, with an M.Sc. in Information Technologies (ÉTS) and a State Engineer degree in Statistics and Applied Economics (INSEA). I design and deploy ML and deep learning solutions for IoT, mobile, and cloud systems, implementing comprehensive MLOps pipelines for model training, deployment, and monitoring, while optimizing performance, memory, and scalability.

Key Skills:

IoT time series analysis and prediction with optimized architectures
ML/DL model development: CNN, RNN, LSTM, Transformers
MLOps pipelines: CI/CD, data versioning, monitoring
Visualization and reporting for data-driven decision making

Industry field of expertise

Languages

French
Native or bilingual
English
Native or bilingual
Arabic
Native or bilingual

Workplace preferences

Can work on-site

Casablanca (up to 50km)

SOWIT
Machine learning engineer
INTERNET OF THINGS (IOT)
November 2025 - Today (7 months)
Casablanca, Morocco
Automatic delimitation of agricultural plots from satellite images
Crop classification via semantic segmentation (Deep Learning)
Anomaly detection & predictive maintenance for agricultural IoT sensors
Data-driven dashboards & scoring for farmers and agricultural holdings
Design of high-performance data pipelines (Kafka, real-time streaming)
Apache Kafka deep-learning Machine learning Data analysis Data Engineering
Ecole de technologie superieure
Machine learning engineer
TECH
January 2023 - September 2025 (2 years and 8 months)
Montréal, Canada
Design and implementation of machine learning models for time series analysis from IoT systems, including the definition of a new architecture optimized for real-time performance, low latency, and low memory footprint. Industrialization via MLOps pipelines (training, deployment, monitoring), enabling fast and scalable processing of IoT data in constrained environments.
Pytorch Python Machine learning Data science Deep Learning
IPTOKI
Data scientist
TECH
September 2021 - January 2023 (1 year and 4 months)
Montréal, Canada
Development and industrialization of machine learning models for behavioral biometric authentication, using data from smartphone IoT sensors (accelerometer, gyroscope). Implementation of MLOps pipelines for training, deployment, and monitoring of models embedded in an Android e-identity application, to detect fraudulent use by impostors.

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Master of Science (M.Sc.) in Information Technologies (Software Engineering and Information Technologies)
École de technologie supérieure (ÉTS)
2023
Machine Learning & Deep Learning, Systèmes IoT et Edge Computing, MLOps & Déploiement, Python, TensorFlow, PyTorch, Keras, ONNX, Docker, Git, plateformes cloud Azure.
State Engineer in Statistics
Institut National de la Statistique et d’Économie Appliquée (INSEA)
2020
Statistique, optimization, mathematiques appliquées

Khalil Snoussi

Machine learning engineer

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