ML Engineer Senior - GenAI Solutions

NTT DATA Europe & Latam; Torino; On-site; EUR 60,000 - 90,000; Full time

Job summary

NTT DATA Europe & Latam is seeking a Senior Machine Learning Engineer. In this role, you will lead ML initiatives, focusing on Generative AI capabilities, and establish scalable processes for data analysis. Candidates should have over 5 years of experience in Data Science or Software Engineering and deep knowledge of mathematical concepts. Proficiency in programming languages such as Python is essential. The role could be located in cities like Torino, Milan, or Bologna with strong collaboration across teams.

Qualifications

• 5+ years of experience in Data Science or Software Engineering.
• Deep knowledge of math, probability, statistics and algorithms.
• Experience in Generative AI deployment for 6-12 months.
• Understanding of data structures, data modeling, and software architecture.
• Fluency in at least two programming languages (Python, Scala, Java, C++).
• Strong knowledge of ML frameworks like Keras or PyTorch.

Responsibilities

• Apply hands-on Generative AI capabilities.
• Establish scalable, automated processes for large-scale data analysis.
• Lead ML Engineers and connect with stakeholders.
• Design and create new data pipelines from scratch.

Skills

Generative AI capabilities

Mathematics

Information retrieval

Clustering

Optimization problems

Data pipelines

Python

Spark

Keras

MLOps

Tools

Azure

GCP

Databricks

Snowflake

Job description

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 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 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 related concepts focusing on 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