Key accomplishments

– Implemented and operationalized AI models (MLOps Pipelines).
– Automated the deployment of models, endpoints and transform jobs on AWS SageMaker.
– Led the architecture design and development of multiple ML projects, ensuring scalability, efficiency,
and maintainability.
– Developed unit tests and refactored code according to standards.
– Collaborated closely with security, compliance, and data governance teams to ensure alignment
regarding the utilization of data within AI projects following DevSecOps principles.
– Developed and deployed web applications (Streamlit).
– Turned Machine Learning Models developed by data scientists into APIs.
– Automated the extraction of advertising data from social media (Facebook and LinkedIn).
– Prepared data for Artificial Intelligence algorithms (Data Pipelines).
– Developed in agile mode and participated in tests.
– Collaborated with cross-functional teams including data scientists, software engineers, and domain
experts to gather requirements and align project objectives.
– Tools and Technologies: Python, R, SQL, Terraform, Docker, Jenkins, Analytics API, Streamlit,
Snowflake, Git, Bitbucket, AWS SageMaker, Lambda, ECR, Step Functions.


Role 1
Machine learning engineer
Role 2
Data scientist
Test Score
AI, Machine learning, Data Science
100%

B2b software and services
Any
Lead
Canada
Any
NA
Remote

Education


Experience


Expertise

Machine Learning Engineering - MLOps - AI
95
Tools and Technologies: Python, R, SQL, Terraform, Docker, Jenkins, Analytics API, Streamlit, Snowflake, Git, Bitbucket, AWS SageMaker, Lambda, ECR, Step Functions.
95

Languages

English,
French,
Arabic