As a Senior Machine Learning Engineer at NTT DATA, you will work alongside experienced Data Scientists, Data and ML Engineers on advanced machine learning and Generative AI initiatives.Your Contribution In This RoleApply hands-on Generative AI capabilities, preferably on Azure/GCP and on-premise GenAI architectures and MLOpsLeverage a strong mathematical backgroundWork on classification, information retrieval, clustering and optimization problemsEstablish scalable, efficient and automated processes for large-scale data analysisContribute to model development, model validation and model implementationIdentify business opportunitiesDesign and create new data pipelines from scratch, from experiments to production deploymentManage multiple projectsLead ML EngineersConnect with stakeholdersThe ideal profileAt least 5 years of production experience working in Data Science or Software Engineering; Deep knowledge of math, probability, statistics and algorithms; At least 6/12 months of experience in Generative AI deployment and underlying architecture handling; Vector Databaseknowledge is well appreciated; Understanding of data structures, data modeling and software architecture; Fluent in at least two mainstream programming languages (Python, Scala, Java, C++); Experience in building an infrastructure for technical users, such as Data Scientist, ML practitioners or data consumers/producers; Strong knowledge of Spark, Databricks is a strong plus; Experience developing/deploying ML solutions in one of the public cloud platforms and on a Cross-cloud base, Snowflake knowledge is a plus; Deep knowledge with machine learning frameworks (such as Keras or PyTorch); Ability to design and implement machine learning pipelines in a production environment; Experience withdeployment including knowledge of CI/CD, containerization, and related concepts with a focus over MLops/Re-Training/Drift Management; Ability to train more junior team members in multiple Machine Learning and Deep Learning concepts; Establish and maintain strong relationships with internal team members and external clientsLocationMilano, Bari, Bologna, Cosenza, Napoli, Pisa, Roma, Torino#J-*****-Ljbffr