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ML Engineer Senior - GenAI Solutions

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Onsite

ML Engineer Senior - GenAI Solutions

NTT DATA BUSINESS SOLUTIONS

ML Engineer Senior - GenAI Solutions

Skills

Google Cloud PlatformDeep LearningPythonData ScienceJavaKerasPyTorchSnowflakeDatabricksData AnalysisMachine LearningAIScalaAzure

2 months ago

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Important information


Contract type:

Permanent

Location:

Bari, Metropolitan City of Bari, Italy

Work mode:

Onsite

Published on:

25 August 2026

What they need


Job Summary

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.

Responsibilities

  • Apply hands-on Generative AI capabilities, preferably on Azure/GCP and onpremise 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 deployment
  • Manage 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 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 a production environment;
  • Experience with deployment 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 clients

Location

Milano, Bari, Bologna, Cosenza, Napoli, Pisa, Roma, Torino

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