J
Jun Saito
About
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São Paulo, State of São Paulo, Brazil
Résumé
Jobs
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Senior Al EngineerRELXSep 2022 - Current (3 years 9 months)• Led design and deployment of production ML services in Python using TensorFlow, PyTorch, and scikit-learn, improving model- driven features for global publishing clients by 27%. • Built end-to-end ML pipelines for NLP and recommendation systems, covering data ingestion, training, evaluation, and deployment with Airflow, Kafka, and Kubernetes-based microservices. • Implemented MLOps practices including CI/CD for ML, automated retraining, and model monitoring, reducing model drift incidents by 35% across key analytics products. • Developed deep learning models for document classification and entity extraction, leveraging transformer-based architectures and LLMs to enhance search relevance in legal research tools. • Collaborated with US-base- Senior Data EngineerHitachiOct 2020 - Aug 2022 (1 year 11 months)• Designed and implemented scalable ML and analytics pipelines in Python for industrial IoT and energy management solutions, using TensorFlow, PyTorch, and scikit-learn where appropriate. • Collaborated with US-based engineering and data science teams to productionize machine learning models that optimized asset performance and predictive maintenance for enterprise clients. • Built robust data ingestion and ETL workflows with Airflow, Kafka, and SQL warehouses, ensuring reliable feature availability for downstream ML systems in manufacturing and rail domains. • Implemented MLOps workflows including containerized deployments with Docker and Kubernetes, automated testing, and blue- green releases for critical Al-powered optimization services.
- SMachine Learning EngineerSynergy LabsOct 2017 - Sep 2020 (3 years)• Developed end-to-end machine learning solutions in Python using scikit-learn and early TensorFlow for clients in e-commerce, ad- tech, and digital media at the consulting-focused lab. • Implemented supervised and unsupervised models for churn prediction, lead scoring, and customer segmentation, integrating outputs into client backend systems via RESTful APIs. • Collaborated with distributed product and engineering teams to translate business problems into ML formulations, selecting appropriate algorithms and evaluation strategies. • Built reproducible training pipelines with versioned datasets, configuration-driven experiments, and automated evaluation, laying groundwork for later MLOps practices. • Applied deep learning techniques for im
- ASoftware EngineerAcompanyJan 2016 - Aug 2017 (1 year 8 months)• Developed and optimized backend services in Python and Java, reducing average API response time by 35% and improving overall system reliability. • Implemented automated data-processing pipelines using R and SQL, cutting manual reporting time by 50% and increasing data accuracy. • Collaborated with cross-functional teams to design a recommendation engine prototype that improved user engagement metrics by 18%. • Created monitoring dashboards and alerts using Grafana and Elastic Stack, enabling faster issue detection and reducing system downtime by 25%.
Education
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- Master of Science, Computer ScienceNagoya UniversityJan 2016 - Dec 2017 (2 years)
- Bachelor of Science, StatisticsNagoya UniversityJan 2015 - Aug 2015 (8 months)