Brussels, Brussels Region, Belgium
With a strong background in automotive and banking sectors, I bring a unique blend of DevOps and ML and Data Engineering expertise to the table. From building robust APIs and automating CI/CD pipelines to enhancing centralized monitoring platforms, I deliver solutions that drive efficiency and innovation. I’m excited to offer my skills as a swiss-knife engineer. Whether you need cutting-edge ML models or streamlined DevOps processes, I’m here to help your projects succeed. Let’s collaborate to bring your vision to life!
Data Engineer in the banking sector * Provided ongoing maintenance and support for the centralized monitoring Data Platform, ensuring continuous and reliable operation. * Monitored system health and performance, proactively addressing issues to minimize downtime and ensure seamless service delivery. * Developed and implemented new features to enhance the platform's monitoring capabilities * Improved data collection and processing pipelines, integrating Kafka for data streaming. Technologies: * Ansible, Linux (Red Hat), Jenkins, Docker, Podman, Elasticsearch, Kibana, Logstash, Filebeat, Metricbeat, Heartbeat, Kafka
DevOps Engineer in the automotive sector * Deploying applications to production environments with a strong emphasis on security and efficiency. * Automated CI/CD pipelines, significantly streamlining the deployment process * Managed and optimized a robust database system that supports multiple applications within the company. * Monitored application performance Technologies: Python, Docker, Kubernetes, AWS, Terraform, Prometheus, Grafana, Bamboo CI/CD, PostgreSQL
ML Engineer in the automotive sector. * Developed a Python-based Vehicle Energy Consumption API, ensuring seamless integration and deployment using Docker on AWS. * Collaborated with DevOps teams to implement secure and efficient cloud deployments. * Spearheaded the development of a Proof of Concept (PoC) for a Road Condition Estimator, utilizing time series analysis, supervised and unsupervised machine learning, and geospatial data analysis to deliver accurate and actionable insights. Technologies: AWS (Athena, SageMaker), Docker, Bamboo CI/CD, python, jupyter
Improving a Computer Vision segmentation model (GridNet) by adding the NLP attention mechanism to the model.
Helping students during mathematics classes to succeed in the admission exam of the Brussels School of Engineering.
- Model Monitoring with Kubernetes, Prometheus and Grafana - Sending ML model to production - MLFlow integration - Technical documentation