Ahmed
From Luxembourg (GMT+2)
8 years of commercial experience
Lemon.io stats
1
projects done670
hours workedOpen
to new offersAhmed – Golang, AI, Kubernetes
Being an ML/Data Science professional with a strong command of English, Ahmed showcased outstanding knowledge during the vetting process at Lemon.io. Experienced in IoT, edge TPUs, computer vision, time series, and NLP, with a background as a Tech Lead and Head of Architecture, Ahmed enjoys hands-on contributions to projects while also valuing interpersonal interactions in his teams. Currently, he is also embarking on authoring a book about Machine Learning!
Main technologies
Additional skills
Rewards and achievements
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Potentially possibleExperience Highlights
Tech Lead
Technical interviewing and assessment platform providing skills assessments and AI-powered learning tools to empower high-performing teams to go beyond skill gaps and help individuals cultivate the skills they need to level up.
• Took leadership of the Data overseeing ML and Data related topics; • Developed and refined comprehensive assessments for evaluating professional skills in machine learning and data science, as a hands-on Senior Machine Learning Engineer; • Designed industry-level machine learning evaluations with an emphasis on MLOps skills, aligning assessment criteria with evolving industry standards; • Continually updated assessment protocols to ensure accurate measurement and relevance to current industry practices.
Senior Machine Learning Engineer
The project involved a leading global provider of space-based data, analytics, and space services and was focused on providing high-resolution weather prediction.
• Delivered a PyTorch-based, HPC-enabled, production-grade weather forecast system; • Spear-headed a research project with the European Space Agency for innovative regional forecasting methods; • Executed a high throughput geographical data ingestion project.
Lead Software Engineer
A GPS high-frequency tracker specifically tailored for the Isle of Man TT bike race.
- Created a pipeline ingesting data from trackers using the LoRaWan protocol through TheThingNetwork;
- Added capabilities for anomaly detection on stream of data.
Data Lead
R&D activity regarding prototyping and testing machine learning functionality for a specific product aimed at boosting the development of financial software.
- Worked on Detecting Drift in Chemical Batch Processes using a Deep Learning approach based on the RNN-LSTM model, incorporating tweaks to enable unsupervised learning;
- Contributed to Multivariate Time Series Reduction, Clustering, and Classification tasks by engineering modified techniques such as 1-NN DTW and Shapelets recognition;
- Developed Sequential Event Patterns Recognition and Prediction capabilities leveraging the WINEPI algorithm;
- Deployed Apache Spark pipelines on Microsoft Azure infrastructure to apply MLlib algorithms across diverse datasets efficiently;
- Revamped the KnowledgeNet software, integrating new data science and machine learning algorithms while enhancing the user experience.