ThiagoCS | DEV & VFX

Thiago Canali leads machine learning engineering initiatives at Spotify, where he architects recommendation, ranking, and search systems at enterprise scale. His work focuses on deploying ML infrastructure that processes user interaction data to generate personalized content suggestions. Prior to Spotify, he developed data science solutions at OLX Group, specializing in marketplace optimization and user behavior analysis. His technical portfolio encompasses production ML systems built with TensorFlow, PyTorch, and cloud-native technologies. At OLX Group, he implemented computer vision models for automated listing classification and natural language processing systems for content moderation. His academic research background includes publications on artificial intelligence applications and data-driven decision systems. Through his personal website and industry presentations, Canali documents practical approaches to machine learning engineering and MLOps. He shares technical documentation about building reliable AI infrastructure, implementing recommendation algorithms, and scaling data pipelines. His work provides concrete examples of enterprise ML architecture patterns and deployment strategies.