Journey
I support two teams in deploying high-traffic models at Wolt, collaborating with the Data Science team to implement robust algorithms and scalable infrastructure for optimized delivery services. My focus on efficient model deployment ensures seamless user experiences and operational excellence, driving innovation in Wolt's machine learning solutions for food delivery.
As a machine learning engineer, I specialize in building advanced NLP models using state-of-the-art methods and OpenAI models. I introduced Kubeflow to improve our machine learning workflows, making them more efficient and scalable. Additionally, I actively engage in knowledge-sharing initiatives to empower my colleagues.
Build, track, version, deploy and monitor ML models. Evaluate models in production using AB and Shadow Testing strategies and use CloudFormation to maintain ML infrastructure. Apply MLOps approaches in order to create scalable and maintainable models.
Build and deploy computer vision models into cutting edge devices for public transport industries.
Teach about agile testing techniques, testing strategies and how to improve the quality in software development life cycle.
Work on a NLP tool that predicts the virality between two headlines.
Create testing strategies through different levels based on the needs and the value for the product. Lead teams to build a high quality products.
Work on a machine learning tool for the TIC department that predicts and provides the variables that influence the most on student retention, and implement a web application to consume the models.