Victor Maso

Machine learning and AI engineer with 7 years of hands-on experience designing, implementing, and scaling production-ready ML solutions across NLP, computer vision, recommender systems, and time-series use cases. Demonstrated success delivering generative AI, large language models, and reinforcement learning systems that increased model performance by up to 30% while driving measurable cost efficiencies. Skilled in transforming traditional analytics workflows into robust, cloud-native AI platforms operating across hybrid, multi-cloud, and edge deployments. Strong technical background in PyTorch, TensorFlow, Hugging Face, Spark, Kafka, Kubeflow, MLflow, and AWS SageMaker. Experienced in LLM adaptation, retrieval-augmented generation architectures, and vector-based search, with a consistent focus on scalable, secure, and explainable AI. Known for effective cross-functional collaboration and mentoring engineers through complex AI initiatives.