SENIOR/LEAD MACHINE LEARNING ENGINEER
Pubblicato il 01-10-2026 - JobLeads in Italia
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. Sebbene l'esperienza competente e le qualifiche siano fondamentali per questo ruolo, si assicuri di verificare di possedere le soft skill preferenziali, se richieste, prima di candidarsi.
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 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 i