Tevos M.

Initially joined as a Machine Learning Engineer, then elected as the Technical Lead to guide the team through key transitions;

Led the evolution of multiple ML projects from proof-of-concept (POC) to minimum viable product (MVP), ensuring scalability and production-readiness;

Spearheaded the transformation of the ML infrastructure into a cloud-agnostic stack, optimizing for flexibility and cost-efficiency;

Architected and managed the development of two Agentic bots, including Retrieval-Augmented Generation (RAG) components;

Oversaw the implementation of a recommendation system and a voice classification model, ensuring robust performance and alignment with business goals;

Established MLOps practices, including CI/CD pipelines, monitoring, and alerting systems to support long-term maintainability and automation;

Facilitated cross-functional collaboration, driving alignment between data science, engineering, and product teams;

Mentored junior engineers and fostered a culture of technical excellence and knowledge sharing within the team.

Set up the backend CI/CD processes for existing computer vision auto-scaled DL model pipelines;

Developed a new DL model to enhance operational functionality within the analytics stack;

Implemented a CI/CD process enabling fast and safe introduction of changes in the full ML lifecycle, critical during the agricultural season;

Optimized processes to achieve cost and latency reduction while maintaining accuracy metrics.

Developed and contributed to packages dedicated to data ETL, ML, and statistical analysis;

Enhanced general operation components of the stack, including GUI-related elements, for team projects;

Worked on structured and unstructured knowledge extraction and NLP tools.