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Ahmed – Golang, AI, Kubernetes, experts in Lemon.io

Ahmed

From Luxembourg (GMT+2)

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Data ScientistStrong senior
Data EngineerSenior
Machine Learning EngineerStrong senior
AI Engineer
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8 years of commercial experience
Aerospace
AI
Automotive
Climate tech
Fintech
Machine learning
Recruiting
Sports
Lemon.io stats
1
projects done
670
hours worked
3
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Ahmed – 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
Golang
5 years
AI
6 years
Kubernetes
5 years
GCP
5 years
AWS
3 years
Data Modeling
7 years
Machine learning
8 years
Data Science
9 years
Python
8 years
Additional skills
Big Data
Algorithms and Data Structures
PyTorch
Tensorflow
Terraform
LLM
GPT
Airflow
BigQuery
MongoDB
Apache Spark
ETL
MLOps
PySpark
Databricks
Data Warehouse
OpenAI
Rewards and achievements
Tech interviewer
Ready to start
ASAP
Direct hire
Potentially possible

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Experience Highlights

Senior Machine Learning Engineer
Apr 2024 - Aug 20244 months
Project Overview

Worked on applying LLM for financial news datasets to extract relevant information.

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Responsibilities:
  • Implemented a pipeline to annotate and label data using spaCy for semi-automatic labelling;
  • Created financial news datasets and used them to fine-tune BERT models;
  • Trained and deployed Deep Learning models trained on data;
  • Created MLOps pipeline to batch process data using Modal in a serverless paradigm.
Project Tech stack:
PyTorch
Python
Machine learning
MongoDB
Databricks
Serverless Computing
MLOps
Tech Lead
Mar 2023 - Dec 20239 months
Project Overview

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.

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Responsibilities:
  • 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.
Project Tech stack:
Python
PyTorch
gRPC
LLM
MLOps
Senior Machine Learning Engineer
Nov 2021 - Oct 202211 months
Project Overview

The project involved a leading global provider of space-based data, analytics, and space services and was focused on providing high-resolution weather prediction.

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Responsibilities:
  • 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;
  • Created a Spark-enabled job to process a high volume of streaming data;
  • Set up MLOps on Databricks, using MLfow and experiment tracking to monitor models and new training;
  • Created API endpoints for ML models using MLflow.
Project Tech stack:
PyTorch
Cloud Computing
Machine learning
Apache Spark
PySpark
AWS
Tensorflow
BigQuery
Big Data
Airflow
Data Warehouse
Data Science
Databricks
MLOps
Lead Software Engineer
May 2019 - Oct 20195 months
Project Overview

A GPS high-frequency tracker specifically tailored for the Isle of Man TT bike race.

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Responsibilities:
  • Created a pipeline ingesting data from trackers using the LoRaWan protocol through TheThingNetwork;
  • Added capabilities for anomaly detection on stream of data.
Project Tech stack:
Golang
gRPC
GCP
Kubernetes
Embedded Systems
BigQuery
GCP Compute Engine
Airflow
Data Lead
Jan 2017 - May 20173 months
Project Overview

R&D activity regarding prototyping and testing machine learning functionality for a specific product aimed at boosting the development of financial software.

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Responsibilities:
  • 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.
Project Tech stack:
pytest
Python
Machine learning

Education

2017
Modeling and Simulation Engineering
Master's

Languages

French
Advanced
Arabic
Advanced
English
Advanced

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