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ML Engineer Senior

Pubblicato il 24-09-2026 - Ntt Data in Milano

Job ID: a1J2p ipd8EAAPosted: Location: Milan, Roma, Turin, Napoli, Cosenza, Bari, Salerno, Bologna, ItaliaSpecialization: C++;JAVA;Python;Cloud;Scala;SparkWork Modality: Híbrido/FlexibleProcess: a072p00001MNAOTAA5Company: NTT DATAOffer DescriptionAs 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 role:Apply 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 stakeholdersRequirementsThe 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 Database knowledge is well appreciated;Understanding of data structures, data modeling and software architecture; Fluent in a at least two mainstream programming language (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

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