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ML Engineer Senior

Pubblicato il 13-08-2026 - Ntt Data Europe & Latam in Roma

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.
Se desidera conoscere i requisiti per questo ruolo, continui a leggere per trovare tutte le informazioni pertinenti. Your Contribution In This Role
- Apply hands‐on Generative AI capabilities, preferably on Azure/GCP and on‐premise GenAI architectures and MLOps
- Leverage a strong mathematical background
- Work on classification, information retrieval, clustering and optimization problems
- Establish scalable, efficient and automated processes for large‐scale data analysis
- Contribute to model development, model validation and model implementation
- Identify business opportunities
- Design and create new data pipelines from scratch, from experiments to production deploymentManage multiple projects
- Lead ML Engineers
- Connect with stakeholders

The ideal profile
- At 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 at least two mainstream programming languages (Python, Scala, Java, C++);
- Experience building infrastructure for technical users such as Data Scientists, 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 xivgfpx knowledge of machine learning frameworks such as Keras or PyTorch;
- Ability to design and implement machine learning pipelines in a production environment;
- Experience with deployment, CI/CD, containerization, and relat

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